Zipf1 New Model Test Data Result Obj Size Ignored
Result
Model Summaries
| Model | Better than base % of the times |
|---|
| LR_7[cache_size=0.01,treshold=0.3] | 0 |
| LR_7[cache_size=0.01,treshold=0.5] | 0 |
| LR_7[cache_size=0.01,treshold=0.6] | 0 |
| LR_7[cache_size=0.01,treshold=0.7] | 0 |
| LR_7[cache_size=0.01,treshold=0.8] | 100 |
| LR_7[cache_size=0.01,treshold=0.9] | 100 |
| LR_8[cache_size=0.01,treshold=0.3] | 0 |
| LR_8[cache_size=0.01,treshold=0.5] | 0 |
| LR_8[cache_size=0.01,treshold=0.6] | 0 |
| LR_8[cache_size=0.01,treshold=0.7] | 0 |
| LR_8[cache_size=0.01,treshold=0.8] | 100 |
| LR_8[cache_size=0.01,treshold=0.9] | 100 |
| LR_9[cache_size=0.01,treshold=0.3] | 0 |
| LR_9[cache_size=0.01,treshold=0.5] | 0 |
| LR_9[cache_size=0.01,treshold=0.6] | 0 |
| LR_9[cache_size=0.01,treshold=0.7] | 0 |
| LR_9[cache_size=0.01,treshold=0.8] | 100 |
| LR_9[cache_size=0.01,treshold=0.9] | 100 |
| LR_7[cache_size=0.1,treshold=0.3] | 0 |
| LR_7[cache_size=0.1,treshold=0.5] | 0 |
| LR_7[cache_size=0.1,treshold=0.6] | 0 |
| LR_7[cache_size=0.1,treshold=0.7] | 0 |
| LR_7[cache_size=0.1,treshold=0.8] | 100 |
| LR_7[cache_size=0.1,treshold=0.9] | 0 |
| LR_8[cache_size=0.1,treshold=0.3] | 0 |
| LR_8[cache_size=0.1,treshold=0.5] | 0 |
| LR_8[cache_size=0.1,treshold=0.6] | 0 |
| LR_8[cache_size=0.1,treshold=0.7] | 0 |
| LR_8[cache_size=0.1,treshold=0.8] | 100 |
| LR_8[cache_size=0.1,treshold=0.9] | 0 |
| LR_9[cache_size=0.1,treshold=0.3] | 0 |
| LR_9[cache_size=0.1,treshold=0.5] | 0 |
| LR_9[cache_size=0.1,treshold=0.6] | 0 |
| LR_9[cache_size=0.1,treshold=0.7] | 0 |
| LR_9[cache_size=0.1,treshold=0.8] | 100 |
| LR_9[cache_size=0.1,treshold=0.9] | 0 |
| LR_7[cache_size=0.2,treshold=0.3] | 0 |
| LR_7[cache_size=0.2,treshold=0.5] | 0 |
| LR_7[cache_size=0.2,treshold=0.6] | 0 |
| LR_7[cache_size=0.2,treshold=0.7] | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 |
| LR_8[cache_size=0.2,treshold=0.3] | 0 |
| LR_8[cache_size=0.2,treshold=0.5] | 0 |
| LR_8[cache_size=0.2,treshold=0.6] | 0 |
| LR_8[cache_size=0.2,treshold=0.7] | 0 |
| LR_8[cache_size=0.2,treshold=0.8] | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 |
| LR_9[cache_size=0.2,treshold=0.3] | 0 |
| LR_9[cache_size=0.2,treshold=0.5] | 0 |
| LR_9[cache_size=0.2,treshold=0.6] | 0 |
| LR_9[cache_size=0.2,treshold=0.7] | 0 |
| LR_9[cache_size=0.2,treshold=0.8] | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 |
| LR_7[cache_size=0.4,treshold=0.3] | 0 |
| LR_7[cache_size=0.4,treshold=0.5] | 0 |
| LR_7[cache_size=0.4,treshold=0.6] | 0 |
| LR_7[cache_size=0.4,treshold=0.7] | 0 |
| LR_7[cache_size=0.4,treshold=0.8] | 0 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 |
| LR_8[cache_size=0.4,treshold=0.3] | 0 |
| LR_8[cache_size=0.4,treshold=0.5] | 0 |
| LR_8[cache_size=0.4,treshold=0.6] | 0 |
| LR_8[cache_size=0.4,treshold=0.7] | 0 |
| LR_8[cache_size=0.4,treshold=0.8] | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 |
| LR_9[cache_size=0.4,treshold=0.3] | 0 |
| LR_9[cache_size=0.4,treshold=0.5] | 0 |
| LR_9[cache_size=0.4,treshold=0.6] | 0 |
| LR_9[cache_size=0.4,treshold=0.7] | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 |
| Offline Clock 1st iteration | 0 |
| Offline Clock 2nd iteration | 100 |
| Zipf Optimal Distribution | 100 |
| Model | Max | Min | Avg | Mdn |
|---|
| LR_7[cache_size=0.01,treshold=0.3] | 72.9112 | 72.8872 | 72.9017 | 72.9019 |
| LR_7[cache_size=0.01,treshold=0.5] | 58.0835 | 58.065 | 58.0713 | 58.0668 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1366 | 46.1098 | 46.1229 | 46.1218 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.7011 | 28.6634 | 28.6839 | 28.6851 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.88137 | 6.86902 | 6.87683 | 6.879 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34773 | 1.34061 | 1.34513 | 1.34701 |
| LR_8[cache_size=0.01,treshold=0.3] | 72.8949 | 72.8688 | 72.8854 | 72.8871 |
| LR_8[cache_size=0.01,treshold=0.5] | 58.1436 | 58.1251 | 58.1344 | 58.1308 |
| LR_8[cache_size=0.01,treshold=0.6] | 46.3455 | 46.3178 | 46.3289 | 46.3244 |
| LR_8[cache_size=0.01,treshold=0.7] | 28.7541 | 28.7157 | 28.7362 | 28.7385 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.72185 | 6.70669 | 6.71479 | 6.71621 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.36124 | 1.35674 | 1.35946 | 1.35994 |
| LR_9[cache_size=0.01,treshold=0.3] | 72.8692 | 72.8397 | 72.8569 | 72.8571 |
| LR_9[cache_size=0.01,treshold=0.5] | 58.3317 | 58.3163 | 58.3231 | 58.3185 |
| LR_9[cache_size=0.01,treshold=0.6] | 46.592 | 46.5631 | 46.5781 | 46.5806 |
| LR_9[cache_size=0.01,treshold=0.7] | 28.6895 | 28.6544 | 28.6731 | 28.6736 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.40022 | 6.38711 | 6.39412 | 6.39562 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.35214 | 1.34658 | 1.34921 | 1.34993 |
| LR_7[cache_size=0.1,treshold=0.3] | 73.4806 | 73.4522 | 73.4674 | 73.4736 |
| LR_7[cache_size=0.1,treshold=0.5] | 59.2362 | 59.1994 | 59.2233 | 59.2247 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.8454 | 47.7884 | 47.822 | 47.8263 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4491 | 30.4138 | 30.4274 | 30.4225 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.21053 | 5.17244 | 5.18877 | 5.18922 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000555101 | 0.000506297 | 0.000531545 | 0.000525669 |
| LR_8[cache_size=0.1,treshold=0.3] | 73.4806 | 73.4536 | 73.4681 | 73.4754 |
| LR_8[cache_size=0.1,treshold=0.5] | 59.2181 | 59.1829 | 59.2057 | 59.2066 |
| LR_8[cache_size=0.1,treshold=0.6] | 47.8241 | 47.7686 | 47.8003 | 47.8032 |
| LR_8[cache_size=0.1,treshold=0.7] | 30.4397 | 30.4058 | 30.4185 | 30.4119 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.23996 | 5.20562 | 5.2224 | 5.22281 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.00056484 | 0.000535507 | 0.000551015 | 0.000545138 |
| LR_9[cache_size=0.1,treshold=0.3] | 73.4937 | 73.4658 | 73.4809 | 73.4873 |
| LR_9[cache_size=0.1,treshold=0.5] | 59.2617 | 59.2255 | 59.249 | 59.2495 |
| LR_9[cache_size=0.1,treshold=0.6] | 47.8607 | 47.8043 | 47.8393 | 47.8454 |
| LR_9[cache_size=0.1,treshold=0.7] | 30.4301 | 30.3941 | 30.409 | 30.4056 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.12955 | 5.09796 | 5.10997 | 5.11123 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000545034 | 0.000516034 | 0.000529597 | 0.000525669 |
| LR_7[cache_size=0.2,treshold=0.3] | 73.8603 | 73.8424 | 73.8544 | 73.856 |
| LR_7[cache_size=0.2,treshold=0.5] | 59.3858 | 59.3529 | 59.3682 | 59.3645 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7083 | 47.6877 | 47.7012 | 47.7035 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8396 | 29.8127 | 29.8321 | 29.8348 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.69871 | 4.62173 | 4.65984 | 4.66176 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.3] | 73.8387 | 73.8212 | 73.8336 | 73.836 |
| LR_8[cache_size=0.2,treshold=0.5] | 59.3779 | 59.3451 | 59.3604 | 59.3574 |
| LR_8[cache_size=0.2,treshold=0.6] | 47.7311 | 47.7086 | 47.7239 | 47.728 |
| LR_8[cache_size=0.2,treshold=0.7] | 29.917 | 29.8913 | 29.9089 | 29.9112 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.83334 | 4.74239 | 4.79185 | 4.79728 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.3] | 73.8693 | 73.8515 | 73.8635 | 73.8653 |
| LR_9[cache_size=0.2,treshold=0.5] | 59.4066 | 59.3738 | 59.3893 | 59.3861 |
| LR_9[cache_size=0.2,treshold=0.6] | 47.7398 | 47.7164 | 47.7314 | 47.7346 |
| LR_9[cache_size=0.2,treshold=0.7] | 29.8617 | 29.8352 | 29.8537 | 29.8565 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.70314 | 4.62542 | 4.6636 | 4.66471 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.3] | 74.2504 | 74.2035 | 74.2236 | 74.2211 |
| LR_7[cache_size=0.4,treshold=0.5] | 59.5458 | 59.4938 | 59.514 | 59.5067 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.1282 | 47.0439 | 47.084 | 47.0885 |
| LR_7[cache_size=0.4,treshold=0.7] | 29.0067 | 28.8549 | 28.9199 | 28.9118 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.85173 | 6.80302 | 6.83317 | 6.84329 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.3] | 74.2465 | 74.1996 | 74.2199 | 74.2175 |
| LR_8[cache_size=0.4,treshold=0.5] | 59.5418 | 59.49 | 59.5097 | 59.5021 |
| LR_8[cache_size=0.4,treshold=0.6] | 47.1254 | 47.0407 | 47.0807 | 47.0844 |
| LR_8[cache_size=0.4,treshold=0.7] | 29.01 | 28.8569 | 28.9221 | 28.9133 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.8552 | 6.80659 | 6.83671 | 6.84693 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.3] | 74.2536 | 74.2062 | 74.2265 | 74.2239 |
| LR_9[cache_size=0.4,treshold=0.5] | 59.5489 | 59.4975 | 59.517 | 59.5096 |
| LR_9[cache_size=0.4,treshold=0.6] | 47.1293 | 47.0449 | 47.0854 | 47.09 |
| LR_9[cache_size=0.4,treshold=0.7] | 29.0014 | 28.849 | 28.9149 | 28.9077 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.845 | 6.79686 | 6.82601 | 6.83324 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 | 0 | 0 |
| Offline Clock 2nd iteration | 43.4673 | 41.4753 | 42.6567 | 43.0175 |
| Zipf Optimal Distribution | 17.0869 | 6.59027 | 12.1282 | 13.1121 |
Miss Ratio Reduced (%)
| Model | Max | Min | Avg | Mdn |
|---|
| LR_7[cache_size=0.01,treshold=0.3] | -5.65544 | -5.67042 | -5.65936 | -5.65663 |
| LR_7[cache_size=0.01,treshold=0.5] | -3.68557 | -3.70064 | -3.69388 | -3.69557 |
| LR_7[cache_size=0.01,treshold=0.6] | -2.43525 | -2.44784 | -2.44125 | -2.44002 |
| LR_7[cache_size=0.01,treshold=0.7] | -1.01491 | -1.02179 | -1.01845 | -1.0189 |
| LR_7[cache_size=0.01,treshold=0.8] | 0.0698421 | 0.0666382 | 0.0684527 | 0.0693389 |
| LR_7[cache_size=0.01,treshold=0.9] | 0.0352876 | 0.0328255 | 0.0341523 | 0.0340449 |
| LR_8[cache_size=0.01,treshold=0.3] | -5.65494 | -5.67042 | -5.65912 | -5.65639 |
| LR_8[cache_size=0.01,treshold=0.5] | -3.6952 | -3.71076 | -3.7035 | -3.70497 |
| LR_8[cache_size=0.01,treshold=0.6] | -2.44932 | -2.46166 | -2.45566 | -2.45458 |
| LR_8[cache_size=0.01,treshold=0.7] | -1.01111 | -1.01808 | -1.0144 | -1.01446 |
| LR_8[cache_size=0.01,treshold=0.8] | 0.0767522 | 0.0742574 | 0.0754115 | 0.0752611 |
| LR_8[cache_size=0.01,treshold=0.9] | 0.0357811 | 0.0335659 | 0.0346951 | 0.034785 |
| LR_9[cache_size=0.01,treshold=0.3] | -5.6581 | -5.67239 | -5.66163 | -5.65865 |
| LR_9[cache_size=0.01,treshold=0.5] | -3.71543 | -3.73001 | -3.72275 | -3.72372 |
| LR_9[cache_size=0.01,treshold=0.6] | -2.46486 | -2.47598 | -2.47012 | -2.46815 |
| LR_9[cache_size=0.01,treshold=0.7] | -0.994186 | -1.00229 | -0.998066 | -0.998416 |
| LR_9[cache_size=0.01,treshold=0.8] | 0.0846408 | 0.0816584 | 0.0833573 | 0.0836508 |
| LR_9[cache_size=0.01,treshold=0.9] | 0.0357811 | 0.0335659 | 0.0346458 | 0.0345383 |
| LR_7[cache_size=0.1,treshold=0.3] | -8.14738 | -8.16586 | -8.15211 | -8.14887 |
| LR_7[cache_size=0.1,treshold=0.5] | -5.06395 | -5.07163 | -5.06717 | -5.06612 |
| LR_7[cache_size=0.1,treshold=0.6] | -3.21156 | -3.22139 | -3.21605 | -3.21626 |
| LR_7[cache_size=0.1,treshold=0.7] | -1.21318 | -1.22114 | -1.21774 | -1.21703 |
| LR_7[cache_size=0.1,treshold=0.8] | 0.107101 | 0.100055 | 0.104549 | 0.104761 |
| LR_7[cache_size=0.1,treshold=0.9] | 0 | -0.000467681 | -0.000280511 | -0.000467327 |
| LR_8[cache_size=0.1,treshold=0.3] | -8.14691 | -8.16539 | -8.15183 | -8.14887 |
| LR_8[cache_size=0.1,treshold=0.5] | -5.06255 | -5.07022 | -5.06567 | -5.06472 |
| LR_8[cache_size=0.1,treshold=0.6] | -3.2111 | -3.21998 | -3.21493 | -3.21486 |
| LR_8[cache_size=0.1,treshold=0.7] | -1.21458 | -1.22254 | -1.21887 | -1.21796 |
| LR_8[cache_size=0.1,treshold=0.8] | 0.106633 | 0.100055 | 0.104268 | 0.104761 |
| LR_8[cache_size=0.1,treshold=0.9] | 0 | -0.000467681 | -0.000280511 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.3] | -8.15076 | -8.1696 | -8.15595 | -8.15308 |
| LR_9[cache_size=0.1,treshold=0.5] | -5.06676 | -5.07443 | -5.07025 | -5.06939 |
| LR_9[cache_size=0.1,treshold=0.6] | -3.2111 | -3.22045 | -3.21558 | -3.21626 |
| LR_9[cache_size=0.1,treshold=0.7] | -1.20897 | -1.21693 | -1.21354 | -1.21329 |
| LR_9[cache_size=0.1,treshold=0.8] | 0.10842 | 0.101458 | 0.105765 | 0.106164 |
| LR_9[cache_size=0.1,treshold=0.9] | 0 | -0.000467681 | -0.000280511 | -0.000467327 |
| LR_7[cache_size=0.2,treshold=0.3] | -9.1235 | -9.12733 | -9.12527 | -9.12554 |
| LR_7[cache_size=0.2,treshold=0.5] | -5.35066 | -5.36681 | -5.35865 | -5.35646 |
| LR_7[cache_size=0.2,treshold=0.6] | -3.21367 | -3.23579 | -3.22569 | -3.22357 |
| LR_7[cache_size=0.2,treshold=0.7] | -1.10015 | -1.11492 | -1.10608 | -1.10351 |
| LR_7[cache_size=0.2,treshold=0.8] | -0.00981444 | -0.0124422 | -0.0117823 | -0.0124353 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.3] | -9.11762 | -9.12144 | -9.11951 | -9.11965 |
| LR_8[cache_size=0.2,treshold=0.5] | -5.35066 | -5.36615 | -5.35839 | -5.35581 |
| LR_8[cache_size=0.2,treshold=0.6] | -3.2189 | -3.24168 | -3.23092 | -3.22881 |
| LR_8[cache_size=0.2,treshold=0.7] | -1.10932 | -1.12212 | -1.1142 | -1.11202 |
| LR_8[cache_size=0.2,treshold=0.8] | -0.011123 | -0.0130933 | -0.012175 | -0.0124358 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.3] | -9.12612 | -9.12995 | -9.12815 | -9.12816 |
| LR_9[cache_size=0.2,treshold=0.5] | -5.35393 | -5.37008 | -5.36205 | -5.35997 |
| LR_9[cache_size=0.2,treshold=0.6] | -3.21628 | -3.23907 | -3.22844 | -3.22619 |
| LR_9[cache_size=0.2,treshold=0.7] | -1.10146 | -1.11623 | -1.10778 | -1.10548 |
| LR_9[cache_size=0.2,treshold=0.8] | -0.0104687 | -0.0130971 | -0.0124369 | -0.0130898 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.3] | -9.49325 | -9.54149 | -9.51692 | -9.51555 |
| LR_7[cache_size=0.4,treshold=0.5] | -5.12316 | -5.18121 | -5.15563 | -5.15518 |
| LR_7[cache_size=0.4,treshold=0.6] | -2.91977 | -2.98173 | -2.9458 | -2.94612 |
| LR_7[cache_size=0.4,treshold=0.7] | -1.04431 | -1.06864 | -1.05688 | -1.0552 |
| LR_7[cache_size=0.4,treshold=0.8] | -0.134606 | -0.159964 | -0.150485 | -0.157828 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.3] | -9.49247 | -9.54104 | -9.51637 | -9.51499 |
| LR_8[cache_size=0.4,treshold=0.5] | -5.12417 | -5.18121 | -5.15596 | -5.15551 |
| LR_8[cache_size=0.4,treshold=0.6] | -2.91977 | -2.98195 | -2.94584 | -2.94589 |
| LR_8[cache_size=0.4,treshold=0.7] | -1.0442 | -1.06819 | -1.05682 | -1.05498 |
| LR_8[cache_size=0.4,treshold=0.8] | -0.134829 | -0.159852 | -0.150596 | -0.158051 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.3] | -9.4938 | -9.54238 | -9.51777 | -9.51655 |
| LR_9[cache_size=0.4,treshold=0.5] | -5.12361 | -5.18166 | -5.15587 | -5.15506 |
| LR_9[cache_size=0.4,treshold=0.6] | -2.91966 | -2.98184 | -2.94555 | -2.94567 |
| LR_9[cache_size=0.4,treshold=0.7] | -1.04398 | -1.06864 | -1.05666 | -1.05476 |
| LR_9[cache_size=0.4,treshold=0.8] | -0.13416 | -0.159964 | -0.150239 | -0.157605 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 | 0 | 0 |
| Offline Clock 2nd iteration | 7.80369 | 0.100977 | 2.73498 | 1.84941 |
| Zipf Optimal Distribution | 3.35401 | 0.0684004 | 1.23463 | 0.902408 |
Model Summaries Plot
Miss Ratio Reduced (%)
Cache Size All
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 42.6567 | 2.73498 |
| Zipf Optimal Distribution | 12.1282 | 1.23463 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.10997 | 0.105765 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18877 | 0.104549 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.2224 | 0.104268 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39412 | 0.0833573 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71479 | 0.0754115 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.87683 | 0.0684527 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35946 | 0.0346951 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34921 | 0.0346458 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34513 | 0.0341523 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000531545 | -0.000280511 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000529597 | -0.000280511 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000551015 | -0.000280511 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.65984 | -0.0117823 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79185 | -0.012175 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.6636 | -0.0124369 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.82601 | -0.150239 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.83317 | -0.150485 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.83671 | -0.150596 |
| LR_9[cache_size=0.01,treshold=0.7] | 28.6731 | -0.998066 |
| LR_8[cache_size=0.01,treshold=0.7] | 28.7362 | -1.0144 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.6839 | -1.01845 |
| LR_9[cache_size=0.4,treshold=0.7] | 28.9149 | -1.05666 |
| LR_8[cache_size=0.4,treshold=0.7] | 28.9221 | -1.05682 |
| LR_7[cache_size=0.4,treshold=0.7] | 28.9199 | -1.05688 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8321 | -1.10608 |
| LR_9[cache_size=0.2,treshold=0.7] | 29.8537 | -1.10778 |
| LR_8[cache_size=0.2,treshold=0.7] | 29.9089 | -1.1142 |
| LR_9[cache_size=0.1,treshold=0.7] | 30.409 | -1.21354 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4274 | -1.21774 |
| LR_8[cache_size=0.1,treshold=0.7] | 30.4185 | -1.21887 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1229 | -2.44125 |
| LR_8[cache_size=0.01,treshold=0.6] | 46.3289 | -2.45566 |
| LR_9[cache_size=0.01,treshold=0.6] | 46.5781 | -2.47012 |
| LR_9[cache_size=0.4,treshold=0.6] | 47.0854 | -2.94555 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.084 | -2.9458 |
| LR_8[cache_size=0.4,treshold=0.6] | 47.0807 | -2.94584 |
| LR_8[cache_size=0.1,treshold=0.6] | 47.8003 | -3.21493 |
| LR_9[cache_size=0.1,treshold=0.6] | 47.8393 | -3.21558 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.822 | -3.21605 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7012 | -3.22569 |
| LR_9[cache_size=0.2,treshold=0.6] | 47.7314 | -3.22844 |
| LR_8[cache_size=0.2,treshold=0.6] | 47.7239 | -3.23092 |
| LR_7[cache_size=0.01,treshold=0.5] | 58.0713 | -3.69388 |
| LR_8[cache_size=0.01,treshold=0.5] | 58.1344 | -3.7035 |
| LR_9[cache_size=0.01,treshold=0.5] | 58.3231 | -3.72275 |
| LR_8[cache_size=0.1,treshold=0.5] | 59.2057 | -5.06567 |
| LR_7[cache_size=0.1,treshold=0.5] | 59.2233 | -5.06717 |
| LR_9[cache_size=0.1,treshold=0.5] | 59.249 | -5.07025 |
| LR_7[cache_size=0.4,treshold=0.5] | 59.514 | -5.15563 |
| LR_9[cache_size=0.4,treshold=0.5] | 59.517 | -5.15587 |
| LR_8[cache_size=0.4,treshold=0.5] | 59.5097 | -5.15596 |
| LR_8[cache_size=0.2,treshold=0.5] | 59.3604 | -5.35839 |
| LR_7[cache_size=0.2,treshold=0.5] | 59.3682 | -5.35865 |
| LR_9[cache_size=0.2,treshold=0.5] | 59.3893 | -5.36205 |
| LR_8[cache_size=0.01,treshold=0.3] | 72.8854 | -5.65912 |
| LR_7[cache_size=0.01,treshold=0.3] | 72.9017 | -5.65936 |
| LR_9[cache_size=0.01,treshold=0.3] | 72.8569 | -5.66163 |
| LR_8[cache_size=0.1,treshold=0.3] | 73.4681 | -8.15183 |
| LR_7[cache_size=0.1,treshold=0.3] | 73.4674 | -8.15211 |
| LR_9[cache_size=0.1,treshold=0.3] | 73.4809 | -8.15595 |
| LR_8[cache_size=0.2,treshold=0.3] | 73.8336 | -9.11951 |
| LR_7[cache_size=0.2,treshold=0.3] | 73.8544 | -9.12527 |
| LR_9[cache_size=0.2,treshold=0.3] | 73.8635 | -9.12815 |
| LR_8[cache_size=0.4,treshold=0.3] | 74.2199 | -9.51637 |
| LR_7[cache_size=0.4,treshold=0.3] | 74.2236 | -9.51692 |
| LR_9[cache_size=0.4,treshold=0.3] | 74.2265 | -9.51777 |
Cache Size 0.01
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 42.0861 | 0.362449 |
| Zipf Optimal Distribution | 8.83002 | 0.192773 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39412 | 0.0833573 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71479 | 0.0754115 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.87683 | 0.0684527 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35946 | 0.0346951 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34921 | 0.0346458 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34513 | 0.0341523 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_9[cache_size=0.01,treshold=0.7] | 28.6731 | -0.998066 |
| LR_8[cache_size=0.01,treshold=0.7] | 28.7362 | -1.0144 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.6839 | -1.01845 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1229 | -2.44125 |
| LR_8[cache_size=0.01,treshold=0.6] | 46.3289 | -2.45566 |
| LR_9[cache_size=0.01,treshold=0.6] | 46.5781 | -2.47012 |
| LR_7[cache_size=0.01,treshold=0.5] | 58.0713 | -3.69388 |
| LR_8[cache_size=0.01,treshold=0.5] | 58.1344 | -3.7035 |
| LR_9[cache_size=0.01,treshold=0.5] | 58.3231 | -3.72275 |
| LR_8[cache_size=0.01,treshold=0.3] | 72.8854 | -5.65912 |
| LR_7[cache_size=0.01,treshold=0.3] | 72.9017 | -5.65936 |
| LR_9[cache_size=0.01,treshold=0.3] | 72.8569 | -5.66163 |
Cache Size 0.1
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.0216 | 1.84971 |
| Zipf Optimal Distribution | 13.1079 | 0.901478 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.10997 | 0.105765 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18877 | 0.104549 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.2224 | 0.104268 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000531545 | -0.000280511 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000551015 | -0.000280511 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000529597 | -0.000280511 |
| LR_9[cache_size=0.1,treshold=0.7] | 30.409 | -1.21354 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4274 | -1.21774 |
| LR_8[cache_size=0.1,treshold=0.7] | 30.4185 | -1.21887 |
| LR_8[cache_size=0.1,treshold=0.6] | 47.8003 | -3.21493 |
| LR_9[cache_size=0.1,treshold=0.6] | 47.8393 | -3.21558 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.822 | -3.21605 |
| LR_8[cache_size=0.1,treshold=0.5] | 59.2057 | -5.06567 |
| LR_7[cache_size=0.1,treshold=0.5] | 59.2233 | -5.06717 |
| LR_9[cache_size=0.1,treshold=0.5] | 59.249 | -5.07025 |
| LR_8[cache_size=0.1,treshold=0.3] | 73.4681 | -8.15183 |
| LR_7[cache_size=0.1,treshold=0.3] | 73.4674 | -8.15211 |
| LR_9[cache_size=0.1,treshold=0.3] | 73.4809 | -8.15595 |
Cache Size 0.2
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.2203 | 3.56227 |
| Zipf Optimal Distribution | 15.0252 | 1.67385 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.65984 | -0.0117823 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79185 | -0.012175 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.6636 | -0.0124369 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8321 | -1.10608 |
| LR_9[cache_size=0.2,treshold=0.7] | 29.8537 | -1.10778 |
| LR_8[cache_size=0.2,treshold=0.7] | 29.9089 | -1.1142 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7012 | -3.22569 |
| LR_9[cache_size=0.2,treshold=0.6] | 47.7314 | -3.22844 |
| LR_8[cache_size=0.2,treshold=0.6] | 47.7239 | -3.23092 |
| LR_8[cache_size=0.2,treshold=0.5] | 59.3604 | -5.35839 |
| LR_7[cache_size=0.2,treshold=0.5] | 59.3682 | -5.35865 |
| LR_9[cache_size=0.2,treshold=0.5] | 59.3893 | -5.36205 |
| LR_8[cache_size=0.2,treshold=0.3] | 73.8336 | -9.11951 |
| LR_7[cache_size=0.2,treshold=0.3] | 73.8544 | -9.12527 |
| LR_9[cache_size=0.2,treshold=0.3] | 73.8635 | -9.12815 |
Cache Size 0.4
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.458 | 7.79849 |
| Zipf Optimal Distribution | 17.0787 | 3.33504 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.82601 | -0.150239 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.83317 | -0.150485 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.83671 | -0.150596 |
| LR_9[cache_size=0.4,treshold=0.7] | 28.9149 | -1.05666 |
| LR_8[cache_size=0.4,treshold=0.7] | 28.9221 | -1.05682 |
| LR_7[cache_size=0.4,treshold=0.7] | 28.9199 | -1.05688 |
| LR_9[cache_size=0.4,treshold=0.6] | 47.0854 | -2.94555 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.084 | -2.9458 |
| LR_8[cache_size=0.4,treshold=0.6] | 47.0807 | -2.94584 |
| LR_7[cache_size=0.4,treshold=0.5] | 59.514 | -5.15563 |
| LR_9[cache_size=0.4,treshold=0.5] | 59.517 | -5.15587 |
| LR_8[cache_size=0.4,treshold=0.5] | 59.5097 | -5.15596 |
| LR_8[cache_size=0.4,treshold=0.3] | 74.2199 | -9.51637 |
| LR_7[cache_size=0.4,treshold=0.3] | 74.2236 | -9.51692 |
| LR_9[cache_size=0.4,treshold=0.3] | 74.2265 | -9.51777 |
Cache Size All
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.0175 | 1.84941 |
| Zipf Optimal Distribution | 13.1121 | 0.902408 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.11123 | 0.106164 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.22281 | 0.104761 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18922 | 0.104761 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39562 | 0.0836508 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71621 | 0.0752611 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.879 | 0.0693389 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35994 | 0.034785 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34993 | 0.0345383 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34701 | 0.0340449 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000545138 | -0.000467327 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.66176 | -0.0124353 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79728 | -0.0124358 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.66471 | -0.0130898 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.83324 | -0.157605 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.84329 | -0.157828 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.84693 | -0.158051 |
| LR_9[cache_size=0.01,treshold=0.7] | 28.6736 | -0.998416 |
| LR_8[cache_size=0.01,treshold=0.7] | 28.7385 | -1.01446 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.6851 | -1.0189 |
| LR_9[cache_size=0.4,treshold=0.7] | 28.9077 | -1.05476 |
| LR_8[cache_size=0.4,treshold=0.7] | 28.9133 | -1.05498 |
| LR_7[cache_size=0.4,treshold=0.7] | 28.9118 | -1.0552 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8348 | -1.10351 |
| LR_9[cache_size=0.2,treshold=0.7] | 29.8565 | -1.10548 |
| LR_8[cache_size=0.2,treshold=0.7] | 29.9112 | -1.11202 |
| LR_9[cache_size=0.1,treshold=0.7] | 30.4056 | -1.21329 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4225 | -1.21703 |
| LR_8[cache_size=0.1,treshold=0.7] | 30.4119 | -1.21796 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1218 | -2.44002 |
| LR_8[cache_size=0.01,treshold=0.6] | 46.3244 | -2.45458 |
| LR_9[cache_size=0.01,treshold=0.6] | 46.5806 | -2.46815 |
| LR_9[cache_size=0.4,treshold=0.6] | 47.09 | -2.94567 |
| LR_8[cache_size=0.4,treshold=0.6] | 47.0844 | -2.94589 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.0885 | -2.94612 |
| LR_8[cache_size=0.1,treshold=0.6] | 47.8032 | -3.21486 |
| LR_9[cache_size=0.1,treshold=0.6] | 47.8454 | -3.21626 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.8263 | -3.21626 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7035 | -3.22357 |
| LR_9[cache_size=0.2,treshold=0.6] | 47.7346 | -3.22619 |
| LR_8[cache_size=0.2,treshold=0.6] | 47.728 | -3.22881 |
| LR_7[cache_size=0.01,treshold=0.5] | 58.0668 | -3.69557 |
| LR_8[cache_size=0.01,treshold=0.5] | 58.1308 | -3.70497 |
| LR_9[cache_size=0.01,treshold=0.5] | 58.3185 | -3.72372 |
| LR_8[cache_size=0.1,treshold=0.5] | 59.2066 | -5.06472 |
| LR_7[cache_size=0.1,treshold=0.5] | 59.2247 | -5.06612 |
| LR_9[cache_size=0.1,treshold=0.5] | 59.2495 | -5.06939 |
| LR_9[cache_size=0.4,treshold=0.5] | 59.5096 | -5.15506 |
| LR_7[cache_size=0.4,treshold=0.5] | 59.5067 | -5.15518 |
| LR_8[cache_size=0.4,treshold=0.5] | 59.5021 | -5.15551 |
| LR_8[cache_size=0.2,treshold=0.5] | 59.3574 | -5.35581 |
| LR_7[cache_size=0.2,treshold=0.5] | 59.3645 | -5.35646 |
| LR_9[cache_size=0.2,treshold=0.5] | 59.3861 | -5.35997 |
| LR_8[cache_size=0.01,treshold=0.3] | 72.8871 | -5.65639 |
| LR_7[cache_size=0.01,treshold=0.3] | 72.9019 | -5.65663 |
| LR_9[cache_size=0.01,treshold=0.3] | 72.8571 | -5.65865 |
| LR_7[cache_size=0.1,treshold=0.3] | 73.4736 | -8.14887 |
| LR_8[cache_size=0.1,treshold=0.3] | 73.4754 | -8.14887 |
| LR_9[cache_size=0.1,treshold=0.3] | 73.4873 | -8.15308 |
| LR_8[cache_size=0.2,treshold=0.3] | 73.836 | -9.11965 |
| LR_7[cache_size=0.2,treshold=0.3] | 73.856 | -9.12554 |
| LR_9[cache_size=0.2,treshold=0.3] | 73.8653 | -9.12816 |
| LR_8[cache_size=0.4,treshold=0.3] | 74.2175 | -9.51499 |
| LR_7[cache_size=0.4,treshold=0.3] | 74.2211 | -9.51555 |
| LR_9[cache_size=0.4,treshold=0.3] | 74.2239 | -9.51655 |
Cache Size 0.01
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 42.0861 | 0.361512 |
| Zipf Optimal Distribution | 8.82408 | 0.192718 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39562 | 0.0836508 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71621 | 0.0752611 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.879 | 0.0693389 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35994 | 0.034785 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34993 | 0.0345383 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34701 | 0.0340449 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_9[cache_size=0.01,treshold=0.7] | 28.6736 | -0.998416 |
| LR_8[cache_size=0.01,treshold=0.7] | 28.7385 | -1.01446 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.6851 | -1.0189 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1218 | -2.44002 |
| LR_8[cache_size=0.01,treshold=0.6] | 46.3244 | -2.45458 |
| LR_9[cache_size=0.01,treshold=0.6] | 46.5806 | -2.46815 |
| LR_7[cache_size=0.01,treshold=0.5] | 58.0668 | -3.69557 |
| LR_8[cache_size=0.01,treshold=0.5] | 58.1308 | -3.70497 |
| LR_9[cache_size=0.01,treshold=0.5] | 58.3185 | -3.72372 |
| LR_8[cache_size=0.01,treshold=0.3] | 72.8871 | -5.65639 |
| LR_7[cache_size=0.01,treshold=0.3] | 72.9019 | -5.65663 |
| LR_9[cache_size=0.01,treshold=0.3] | 72.8571 | -5.65865 |
Cache Size 0.1
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.0175 | 1.84941 |
| Zipf Optimal Distribution | 13.1121 | 0.902408 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.11123 | 0.106164 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.22281 | 0.104761 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18922 | 0.104761 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000545138 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.7] | 30.4056 | -1.21329 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4225 | -1.21703 |
| LR_8[cache_size=0.1,treshold=0.7] | 30.4119 | -1.21796 |
| LR_8[cache_size=0.1,treshold=0.6] | 47.8032 | -3.21486 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.8263 | -3.21626 |
| LR_9[cache_size=0.1,treshold=0.6] | 47.8454 | -3.21626 |
| LR_8[cache_size=0.1,treshold=0.5] | 59.2066 | -5.06472 |
| LR_7[cache_size=0.1,treshold=0.5] | 59.2247 | -5.06612 |
| LR_9[cache_size=0.1,treshold=0.5] | 59.2495 | -5.06939 |
| LR_7[cache_size=0.1,treshold=0.3] | 73.4736 | -8.14887 |
| LR_8[cache_size=0.1,treshold=0.3] | 73.4754 | -8.14887 |
| LR_9[cache_size=0.1,treshold=0.3] | 73.4873 | -8.15308 |
Cache Size 0.2
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.2233 | 3.56334 |
| Zipf Optimal Distribution | 15.0351 | 1.67163 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.66176 | -0.0124353 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79728 | -0.0124358 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.66471 | -0.0130898 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8348 | -1.10351 |
| LR_9[cache_size=0.2,treshold=0.7] | 29.8565 | -1.10548 |
| LR_8[cache_size=0.2,treshold=0.7] | 29.9112 | -1.11202 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7035 | -3.22357 |
| LR_9[cache_size=0.2,treshold=0.6] | 47.7346 | -3.22619 |
| LR_8[cache_size=0.2,treshold=0.6] | 47.728 | -3.22881 |
| LR_8[cache_size=0.2,treshold=0.5] | 59.3574 | -5.35581 |
| LR_7[cache_size=0.2,treshold=0.5] | 59.3645 | -5.35646 |
| LR_9[cache_size=0.2,treshold=0.5] | 59.3861 | -5.35997 |
| LR_8[cache_size=0.2,treshold=0.3] | 73.836 | -9.11965 |
| LR_7[cache_size=0.2,treshold=0.3] | 73.856 | -9.12554 |
| LR_9[cache_size=0.2,treshold=0.3] | 73.8653 | -9.12816 |
Cache Size 0.4
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.46 | 7.8007 |
| Zipf Optimal Distribution | 17.0793 | 3.33616 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.83324 | -0.157605 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.84329 | -0.157828 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.84693 | -0.158051 |
| LR_9[cache_size=0.4,treshold=0.7] | 28.9077 | -1.05476 |
| LR_8[cache_size=0.4,treshold=0.7] | 28.9133 | -1.05498 |
| LR_7[cache_size=0.4,treshold=0.7] | 28.9118 | -1.0552 |
| LR_9[cache_size=0.4,treshold=0.6] | 47.09 | -2.94567 |
| LR_8[cache_size=0.4,treshold=0.6] | 47.0844 | -2.94589 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.0885 | -2.94612 |
| LR_9[cache_size=0.4,treshold=0.5] | 59.5096 | -5.15506 |
| LR_7[cache_size=0.4,treshold=0.5] | 59.5067 | -5.15518 |
| LR_8[cache_size=0.4,treshold=0.5] | 59.5021 | -5.15551 |
| LR_8[cache_size=0.4,treshold=0.3] | 74.2175 | -9.51499 |
| LR_7[cache_size=0.4,treshold=0.3] | 74.2211 | -9.51555 |
| LR_9[cache_size=0.4,treshold=0.3] | 74.2239 | -9.51655 |
Model Classification Report
LR_7
0.01
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.47 0.62 28055468
1 0.58 0.95 0.72 21729815
accuracy 0.68 49785283
macro avg 0.75 0.71 0.67 49785283
weighted avg 0.77 0.68 0.66 49785283
Accuracy: 0.6755959587494963
0-1%
precision recall f1-score support
0 0.92 0.47 0.62 27764588
1 0.52 0.93 0.67 17098553
accuracy 0.65 44863141
macro avg 0.72 0.70 0.64 44863141
weighted avg 0.77 0.65 0.64 44863141
Accuracy: 0.6464878150194611
1-10%
precision recall f1-score support
0 0.00 0.00 0.00 287564
1 0.94 1.00 0.97 4164787
accuracy 0.94 4452351
macro avg 0.47 0.50 0.48 4452351
weighted avg 0.87 0.94 0.90 4452351
Accuracy: 0.9354129986607076
10-20%
precision recall f1-score support
0 0.00 0.00 0.00 2455
1 0.99 1.00 1.00 257616
accuracy 0.99 260071
macro avg 0.50 0.50 0.50 260071
weighted avg 0.98 0.99 0.99 260071
Accuracy: 0.9905602700800935
20-40%
precision recall f1-score support
0 0.00 0.00 0.00 659
1 0.99 1.00 1.00 130568
accuracy 0.99 131227
macro avg 0.50 0.50 0.50 131227
weighted avg 0.99 0.99 0.99 131227
Accuracy: 0.9949781676027037
40-80%
precision recall f1-score support
0 0.00 0.00 0.00 169
1 1.00 1.00 1.00 65234
accuracy 1.00 65403
macro avg 0.50 0.50 0.50 65403
weighted avg 0.99 1.00 1.00 65403
Accuracy: 0.9974160206718347
80-90%
precision recall f1-score support
0 0.00 0.00 0.00 15
1 1.00 1.00 1.00 7371
accuracy 1.00 7386
macro avg 0.50 0.50 0.50 7386
weighted avg 1.00 1.00 1.00 7386
Accuracy: 0.9979691307879772
90-100%
precision recall f1-score support
0 0.00 0.00 0.00 18
1 1.00 1.00 1.00 5686
accuracy 1.00 5704
macro avg 0.50 0.50 0.50 5704
weighted avg 0.99 1.00 1.00 5704
Accuracy: 0.9968443197755961
Treshold: 0.5
All
precision recall f1-score support
0 0.84 0.64 0.72 28055468
1 0.64 0.84 0.73 21729815
accuracy 0.73 49785283
macro avg 0.74 0.74 0.73 49785283
weighted avg 0.75 0.73 0.73 49785283
Accuracy: 0.726206618128494
precision recall f1-score support
0 0.84 0.64 0.72 28055468
1 0.64 0.84 0.73 21729815
accuracy 0.73 49785283
macro avg 0.74 0.74 0.73 49785283
weighted avg 0.75 0.73 0.73 49785283
Accuracy: 0.7262065980422368
0-1%
precision recall f1-score support
0 0.84 0.65 0.73 27764588
1 0.58 0.80 0.67 17098553
accuracy 0.70 44863141
macro avg 0.71 0.72 0.70 44863141
weighted avg 0.74 0.70 0.71 44863141
Accuracy: 0.7031807469744483
precision recall f1-score support
0 0.84 0.65 0.73 27764588
1 0.58 0.80 0.67 17098553
accuracy 0.70 44863141
macro avg 0.71 0.72 0.70 44863141
weighted avg 0.74 0.70 0.71 44863141
Accuracy: 0.7031807246844353
1-10%
precision recall f1-score support
0 0.09 0.01 0.02 287564
1 0.94 0.99 0.96 4164787
accuracy 0.93 4452351
macro avg 0.51 0.50 0.49 4452351
weighted avg 0.88 0.93 0.90 4452351
Accuracy: 0.9303529753157377
precision recall f1-score support
0 0.84 0.64 0.72 28052152
1 0.64 0.83 0.72 21263340
accuracy 0.72 49315492
macro avg 0.74 0.74 0.72 49315492
weighted avg 0.75 0.72 0.72 49315492
Accuracy: 0.7236905392731355
10-20%
precision recall f1-score support
0 0.84 0.64 0.72 28054607
1 0.64 0.84 0.73 21520956
accuracy 0.73 49575563
macro avg 0.74 0.74 0.73 49575563
weighted avg 0.75 0.73 0.73 49575563
Accuracy: 0.7250804393285458
precision recall f1-score support
0 0.01 0.00 0.00 2455
1 0.99 1.00 0.99 257616
accuracy 0.99 260071
macro avg 0.50 0.50 0.50 260071
weighted avg 0.98 0.99 0.98 260071
Accuracy: 0.988637718161579
20-40%
precision recall f1-score support
0 0.84 0.64 0.72 28055266
1 0.64 0.84 0.73 21651524
accuracy 0.73 49706790
macro avg 0.74 0.74 0.73 49706790
weighted avg 0.75 0.73 0.73 49706790
Accuracy: 0.7257862959969855
precision recall f1-score support
0 0.01 0.00 0.01 659
1 0.99 1.00 1.00 130568
accuracy 0.99 131227
macro avg 0.50 0.50 0.50 131227
weighted avg 0.99 0.99 0.99 131227
Accuracy: 0.9924482004465545
40-80%
precision recall f1-score support
0 0.84 0.64 0.72 28055435
1 0.64 0.84 0.73 21716758
accuracy 0.73 49772193
macro avg 0.74 0.74 0.73 49772193
weighted avg 0.75 0.73 0.73 49772193
Accuracy: 0.7261369214734018
precision recall f1-score support
0 0.00 0.00 0.00 169
1 1.00 1.00 1.00 65234
accuracy 0.99 65403
macro avg 0.50 0.50 0.50 65403
weighted avg 0.99 0.99 0.99 65403
Accuracy: 0.9926150176597404
80-90%
precision recall f1-score support
0 0.00 0.00 0.00 15
1 1.00 0.99 1.00 7371
accuracy 0.99 7386
macro avg 0.50 0.50 0.50 7386
weighted avg 1.00 0.99 0.99 7386
Accuracy: 0.9928242621175196
90-100%
precision recall f1-score support
0 0.00 0.00 0.00 18
1 1.00 0.99 0.99 5686
accuracy 0.99 5704
macro avg 0.50 0.50 0.50 5704
weighted avg 0.99 0.99 0.99 5704
Accuracy: 0.9891304347826086
Treshold: 0.6
All
precision recall f1-score support
0 0.77 0.75 0.76 28055468
1 0.69 0.72 0.70 21729815
accuracy 0.74 49785283
macro avg 0.73 0.73 0.73 49785283
weighted avg 0.74 0.74 0.74 49785283
Accuracy: 0.7355653276089643
0-1%
precision recall f1-score support
0 0.78 0.76 0.77 27764588
1 0.62 0.65 0.64 17098553
accuracy 0.72 44863141
macro avg 0.70 0.70 0.70 44863141
weighted avg 0.72 0.72 0.72 44863141
Accuracy: 0.7159792266885637
1-10%
precision recall f1-score support
0 0.09 0.05 0.06 287564
1 0.94 0.97 0.95 4164787
accuracy 0.91 4452351
macro avg 0.51 0.51 0.51 4452351
weighted avg 0.88 0.91 0.89 4452351
Accuracy: 0.9077972513847179
10-20%
precision recall f1-score support
0 0.01 0.02 0.01 2455
1 0.99 0.99 0.99 257616
accuracy 0.98 260071
macro avg 0.50 0.50 0.50 260071
weighted avg 0.98 0.98 0.98 260071
Accuracy: 0.9765948529440037
20-40%
precision recall f1-score support
0 0.01 0.03 0.01 659
1 1.00 0.98 0.99 130568
accuracy 0.97 131227
macro avg 0.50 0.50 0.50 131227
weighted avg 0.99 0.97 0.98 131227
Accuracy: 0.9748755972475177
40-80%
precision recall f1-score support
0 0.00 0.05 0.01 169
1 1.00 0.97 0.98 65234
accuracy 0.96 65403
macro avg 0.50 0.51 0.49 65403
weighted avg 0.99 0.96 0.98 65403
Accuracy: 0.9638854486797241
80-90%
precision recall f1-score support
0 0.00 0.07 0.01 15
1 1.00 0.96 0.98 7371
accuracy 0.95 7386
macro avg 0.50 0.51 0.49 7386
weighted avg 1.00 0.95 0.97 7386
Accuracy: 0.9545085296506904
90-100%
precision recall f1-score support
0 0.00 0.06 0.01 18
1 1.00 0.95 0.97 5686
accuracy 0.95 5704
macro avg 0.50 0.50 0.49 5704
weighted avg 0.99 0.95 0.97 5704
Accuracy: 0.9491584852734923
Treshold: 0.7
All
precision recall f1-score support
0 0.69 0.88 0.77 28055468
1 0.76 0.50 0.60 21729815
accuracy 0.71 49785283
macro avg 0.73 0.69 0.69 49785283
weighted avg 0.72 0.71 0.70 49785283
Accuracy: 0.7110544294786875
0-1%
precision recall f1-score support
0 0.70 0.88 0.78 27764588
1 0.68 0.39 0.50 17098553
accuracy 0.70 44863141
macro avg 0.69 0.64 0.64 44863141
weighted avg 0.69 0.70 0.67 44863141
Accuracy: 0.6968400406917563
1-10%
precision recall f1-score support
0 0.08 0.16 0.11 287564
1 0.94 0.88 0.91 4164787
accuracy 0.83 4452351
macro avg 0.51 0.52 0.51 4452351
weighted avg 0.88 0.83 0.86 4452351
Accuracy: 0.8325159000267499
10-20%
precision recall f1-score support
0 0.01 0.06 0.02 2455
1 0.99 0.94 0.97 257616
accuracy 0.93 260071
macro avg 0.50 0.50 0.49 260071
weighted avg 0.98 0.93 0.96 260071
Accuracy: 0.934371767709587
20-40%
precision recall f1-score support
0 0.01 0.10 0.01 659
1 1.00 0.92 0.95 130568
accuracy 0.91 131227
macro avg 0.50 0.51 0.48 131227
weighted avg 0.99 0.91 0.95 131227
Accuracy: 0.9129371242198633
40-80%
precision recall f1-score support
0 0.00 0.17 0.01 169
1 1.00 0.87 0.93 65234
accuracy 0.87 65403
macro avg 0.50 0.52 0.47 65403
weighted avg 0.99 0.87 0.93 65403
Accuracy: 0.8724676238093054
80-90%
precision recall f1-score support
0 0.00 0.13 0.00 15
1 1.00 0.85 0.92 7371
accuracy 0.85 7386
macro avg 0.50 0.49 0.46 7386
weighted avg 1.00 0.85 0.92 7386
Accuracy: 0.8479555916598971
90-100%
precision recall f1-score support
0 0.01 0.33 0.01 18
1 1.00 0.85 0.92 5686
accuracy 0.85 5704
macro avg 0.50 0.59 0.47 5704
weighted avg 0.99 0.85 0.91 5704
Accuracy: 0.8467741935483871
Treshold: 0.8
All
precision recall f1-score support
0 0.60 0.99 0.75 28055468
1 0.90 0.16 0.27 21729815
accuracy 0.62 49785283
macro avg 0.75 0.57 0.51 49785283
weighted avg 0.73 0.62 0.54 49785283
Accuracy: 0.623849602301146
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.78 0.05 0.10 17098553
accuracy 0.63 44863141
macro avg 0.70 0.52 0.43 44863141
weighted avg 0.69 0.63 0.51 44863141
Accuracy: 0.6327755785088699
1-10%
precision recall f1-score support
0 0.07 0.56 0.13 287564
1 0.94 0.52 0.67 4164787
accuracy 0.53 4452351
macro avg 0.51 0.54 0.40 4452351
weighted avg 0.89 0.53 0.64 4452351
Accuracy: 0.5269303790289669
10-20%
precision recall f1-score support
0 0.01 0.24 0.02 2455
1 0.99 0.76 0.86 257616
accuracy 0.76 260071
macro avg 0.50 0.50 0.44 260071
weighted avg 0.98 0.76 0.85 260071
Accuracy: 0.7580468410549427
20-40%
precision recall f1-score support
0 0.01 0.36 0.01 659
1 1.00 0.67 0.80 130568
accuracy 0.66 131227
macro avg 0.50 0.51 0.40 131227
weighted avg 0.99 0.66 0.79 131227
Accuracy: 0.6645354995542075
40-80%
precision recall f1-score support
0 0.00 0.51 0.01 169
1 1.00 0.52 0.69 65234
accuracy 0.52 65403
macro avg 0.50 0.52 0.35 65403
weighted avg 0.99 0.52 0.68 65403
Accuracy: 0.5224072290261914
80-90%
precision recall f1-score support
0 0.00 0.47 0.00 15
1 1.00 0.43 0.60 7371
accuracy 0.43 7386
macro avg 0.50 0.45 0.30 7386
weighted avg 1.00 0.43 0.60 7386
Accuracy: 0.4309504467912266
90-100%
precision recall f1-score support
0 0.00 0.56 0.01 18
1 1.00 0.43 0.60 5686
accuracy 0.43 5704
macro avg 0.50 0.49 0.30 5704
weighted avg 0.99 0.43 0.60 5704
Accuracy: 0.42934782608695654
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 28055468
1 0.95 0.03 0.06 21729815
accuracy 0.58 49785283
macro avg 0.76 0.51 0.39 49785283
weighted avg 0.74 0.58 0.44 49785283
Accuracy: 0.5762185784903543
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.55 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.58 0.50 0.38 44863141
weighted avg 0.59 0.62 0.47 44863141
Accuracy: 0.6189122602895771
1-10%
precision recall f1-score support
0 0.07 0.92 0.13 287564
1 0.96 0.14 0.24 4164787
accuracy 0.19 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.19 0.23 4452351
Accuracy: 0.18617085670020175
10-20%
precision recall f1-score support
0 0.01 0.69 0.02 2455
1 0.99 0.30 0.46 257616
accuracy 0.31 260071
macro avg 0.50 0.50 0.24 260071
weighted avg 0.98 0.31 0.46 260071
Accuracy: 0.30700078055607893
20-40%
precision recall f1-score support
0 0.00 0.90 0.01 659
1 0.99 0.09 0.16 130568
accuracy 0.09 131227
macro avg 0.50 0.49 0.08 131227
weighted avg 0.99 0.09 0.16 131227
Accuracy: 0.08976811174529632
40-80%
precision recall f1-score support
0 0.00 1.00 0.01 169
1 1.00 0.00 0.00 65234
accuracy 0.00 65403
macro avg 0.50 0.50 0.00 65403
weighted avg 1.00 0.00 0.00 65403
Accuracy: 0.004648104826995704
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 0.00 0.00 0.00 7371
accuracy 0.00 7386
macro avg 0.00 0.50 0.00 7386
weighted avg 0.00 0.00 0.00 7386
Accuracy: 0.0020308692120227455
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 0.00 0.00 0.00 5686
accuracy 0.00 5704
macro avg 0.00 0.50 0.00 5704
weighted avg 0.00 0.00 0.00 5704
Accuracy: 0.003155680224403927
0.1
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.48 0.63 26119367
1 0.60 0.95 0.73 21615229
accuracy 0.69 47734596
macro avg 0.76 0.71 0.68 47734596
weighted avg 0.77 0.69 0.68 47734596
Accuracy: 0.6900191844087252
0-1%
precision recall f1-score support
0 0.97 0.82 0.89 12053010
1 0.08 0.40 0.14 508421
accuracy 0.80 12561431
macro avg 0.53 0.61 0.51 12561431
weighted avg 0.93 0.80 0.86 12561431
Accuracy: 0.7982386720111745
1-10%
precision recall f1-score support
0 0.76 0.20 0.31 13368467
1 0.56 0.94 0.70 14466820
accuracy 0.59 27835287
macro avg 0.66 0.57 0.51 27835287
weighted avg 0.66 0.59 0.52 27835287
Accuracy: 0.5850499763124412
10-20%
precision recall f1-score support
0 0.28 0.01 0.02 503365
1 0.87 1.00 0.93 3387274
accuracy 0.87 3890639
macro avg 0.57 0.50 0.47 3890639
weighted avg 0.79 0.87 0.81 3890639
Accuracy: 0.8686038463090511
20-40%
precision recall f1-score support
0 0.24 0.01 0.02 147488
1 0.93 1.00 0.96 1970425
accuracy 0.93 2117913
macro avg 0.58 0.50 0.49 2117913
weighted avg 0.88 0.93 0.90 2117913
Accuracy: 0.9285036731914862
40-80%
precision recall f1-score support
0 0.21 0.02 0.03 41616
1 0.96 1.00 0.98 1064279
accuracy 0.96 1105895
macro avg 0.59 0.51 0.51 1105895
weighted avg 0.93 0.96 0.94 1105895
Accuracy: 0.960486302949195
80-90%
precision recall f1-score support
0 0.22 0.03 0.05 3093
1 0.98 1.00 0.99 120943
accuracy 0.97 124036
macro avg 0.60 0.51 0.52 124036
weighted avg 0.96 0.97 0.96 124036
Accuracy: 0.9732980747524912
90-100%
precision recall f1-score support
0 0.22 0.03 0.05 2328
1 0.98 1.00 0.99 97067
accuracy 0.97 99395
macro avg 0.60 0.51 0.52 99395
weighted avg 0.96 0.97 0.97 99395
Accuracy: 0.9748780119724332
Treshold: 0.5
All
precision recall f1-score support
0 0.83 0.64 0.73 26119367
1 0.66 0.85 0.74 21615229
accuracy 0.73 47734596
macro avg 0.75 0.74 0.73 47734596
weighted avg 0.76 0.73 0.73 47734596
Accuracy: 0.7341488131584899
precision recall f1-score support
0 0.83 0.64 0.73 26119367
1 0.66 0.85 0.74 21615229
accuracy 0.73 47734596
macro avg 0.75 0.74 0.73 47734596
weighted avg 0.76 0.73 0.73 47734596
Accuracy: 0.7341488131584899
0-1%
precision recall f1-score support
0 0.97 0.91 0.94 12053010
1 0.10 0.23 0.14 508421
accuracy 0.88 12561431
macro avg 0.53 0.57 0.54 12561431
weighted avg 0.93 0.88 0.90 12561431
Accuracy: 0.8825039121737006
precision recall f1-score support
0 0.97 0.91 0.94 12053010
1 0.10 0.23 0.14 508421
accuracy 0.88 12561431
macro avg 0.53 0.57 0.54 12561431
weighted avg 0.93 0.88 0.90 12561431
Accuracy: 0.8825039121737006
1-10%
precision recall f1-score support
0 0.84 0.66 0.74 25421477
1 0.58 0.79 0.67 14975241
accuracy 0.71 40396718
macro avg 0.71 0.72 0.70 40396718
weighted avg 0.74 0.71 0.71 40396718
Accuracy: 0.7066286919645304
precision recall f1-score support
0 0.68 0.43 0.53 13368467
1 0.61 0.81 0.69 14466820
accuracy 0.63 27835287
macro avg 0.64 0.62 0.61 27835287
weighted avg 0.64 0.63 0.61 27835287
Accuracy: 0.6272601751869847
10-20%
precision recall f1-score support
0 0.84 0.65 0.73 25924842
1 0.62 0.82 0.71 18362515
accuracy 0.72 44287357
macro avg 0.73 0.73 0.72 44287357
weighted avg 0.75 0.72 0.72 44287357
Accuracy: 0.7193548488341718
precision recall f1-score support
0 0.20 0.05 0.08 503365
1 0.87 0.97 0.92 3387274
accuracy 0.85 3890639
macro avg 0.54 0.51 0.50 3890639
weighted avg 0.79 0.85 0.81 3890639
Accuracy: 0.851491233188173
20-40%
precision recall f1-score support
0 0.84 0.64 0.73 26072330
1 0.65 0.84 0.73 20332940
accuracy 0.73 46405270
macro avg 0.74 0.74 0.73 46405270
weighted avg 0.75 0.73 0.73 46405270
Accuracy: 0.7281251461310321
precision recall f1-score support
0 0.12 0.04 0.06 147488
1 0.93 0.98 0.95 1970425
accuracy 0.91 2117913
macro avg 0.53 0.51 0.51 2117913
weighted avg 0.88 0.91 0.89 2117913
Accuracy: 0.9115195005649429
40-80%
precision recall f1-score support
0 0.83 0.64 0.73 26113946
1 0.66 0.84 0.74 21397219
accuracy 0.73 47511165
macro avg 0.75 0.74 0.73 47511165
weighted avg 0.76 0.73 0.73 47511165
Accuracy: 0.7331112802643337
precision recall f1-score support
0 0.07 0.05 0.06 41616
1 0.96 0.98 0.97 1064279
accuracy 0.94 1105895
macro avg 0.52 0.51 0.51 1105895
weighted avg 0.93 0.94 0.94 1105895
Accuracy: 0.9423381062397425
80-90%
precision recall f1-score support
0 0.06 0.06 0.06 3093
1 0.98 0.98 0.98 120943
accuracy 0.95 124036
macro avg 0.52 0.52 0.52 124036
weighted avg 0.95 0.95 0.95 124036
Accuracy: 0.9538601696281724
90-100%
precision recall f1-score support
0 0.06 0.06 0.06 2328
1 0.98 0.98 0.98 97067
accuracy 0.96 99395
macro avg 0.52 0.52 0.52 99395
weighted avg 0.96 0.96 0.96 99395
Accuracy: 0.9559233361839127
Treshold: 0.6
All
precision recall f1-score support
0 0.77 0.74 0.76 26119367
1 0.70 0.74 0.72 21615229
accuracy 0.74 47734596
macro avg 0.74 0.74 0.74 47734596
weighted avg 0.74 0.74 0.74 47734596
Accuracy: 0.7409564124099846
0-1%
precision recall f1-score support
0 0.96 0.95 0.96 12053010
1 0.11 0.15 0.13 508421
accuracy 0.92 12561431
macro avg 0.54 0.55 0.54 12561431
weighted avg 0.93 0.92 0.92 12561431
Accuracy: 0.9175185534195905
1-10%
precision recall f1-score support
0 0.62 0.59 0.61 13368467
1 0.64 0.67 0.65 14466820
accuracy 0.63 27835287
macro avg 0.63 0.63 0.63 27835287
weighted avg 0.63 0.63 0.63 27835287
Accuracy: 0.6313560194295823
10-20%
precision recall f1-score support
0 0.18 0.11 0.14 503365
1 0.88 0.93 0.90 3387274
accuracy 0.82 3890639
macro avg 0.53 0.52 0.52 3890639
weighted avg 0.79 0.82 0.80 3890639
Accuracy: 0.8202835061284277
20-40%
precision recall f1-score support
0 0.10 0.09 0.10 147488
1 0.93 0.94 0.94 1970425
accuracy 0.88 2117913
macro avg 0.52 0.52 0.52 2117913
weighted avg 0.87 0.88 0.88 2117913
Accuracy: 0.8809167326514357
40-80%
precision recall f1-score support
0 0.06 0.09 0.07 41616
1 0.96 0.94 0.95 1064279
accuracy 0.91 1105895
macro avg 0.51 0.52 0.51 1105895
weighted avg 0.93 0.91 0.92 1105895
Accuracy: 0.9104318221892675
80-90%
precision recall f1-score support
0 0.04 0.10 0.06 3093
1 0.98 0.94 0.96 120943
accuracy 0.92 124036
macro avg 0.51 0.52 0.51 124036
weighted avg 0.95 0.92 0.94 124036
Accuracy: 0.9208778096681609
90-100%
precision recall f1-score support
0 0.04 0.10 0.06 2328
1 0.98 0.94 0.96 97067
accuracy 0.92 99395
macro avg 0.51 0.52 0.51 99395
weighted avg 0.96 0.92 0.94 99395
Accuracy: 0.9229538709190603
Treshold: 0.7
All
precision recall f1-score support
0 0.69 0.86 0.77 26119367
1 0.76 0.54 0.63 21615229
accuracy 0.71 47734596
macro avg 0.73 0.70 0.70 47734596
weighted avg 0.72 0.71 0.71 47734596
Accuracy: 0.7148622981956315
0-1%
precision recall f1-score support
0 0.96 0.98 0.97 12053010
1 0.15 0.08 0.10 508421
accuracy 0.95 12561431
macro avg 0.56 0.53 0.54 12561431
weighted avg 0.93 0.95 0.94 12561431
Accuracy: 0.9455314446260144
1-10%
precision recall f1-score support
0 0.56 0.78 0.65 13368467
1 0.68 0.43 0.53 14466820
accuracy 0.60 27835287
macro avg 0.62 0.60 0.59 27835287
weighted avg 0.62 0.60 0.59 27835287
Accuracy: 0.5979200430015326
10-20%
precision recall f1-score support
0 0.17 0.28 0.21 503365
1 0.88 0.79 0.84 3387274
accuracy 0.73 3890639
macro avg 0.53 0.54 0.52 3890639
weighted avg 0.79 0.73 0.76 3890639
Accuracy: 0.7282690581161604
20-40%
precision recall f1-score support
0 0.10 0.23 0.14 147488
1 0.94 0.83 0.88 1970425
accuracy 0.79 2117913
macro avg 0.52 0.53 0.51 2117913
weighted avg 0.88 0.79 0.83 2117913
Accuracy: 0.7927138650171183
40-80%
precision recall f1-score support
0 0.05 0.23 0.09 41616
1 0.97 0.84 0.90 1064279
accuracy 0.82 1105895
macro avg 0.51 0.53 0.49 1105895
weighted avg 0.93 0.82 0.87 1105895
Accuracy: 0.8195850419795732
80-90%
precision recall f1-score support
0 0.04 0.24 0.06 3093
1 0.98 0.84 0.90 120943
accuracy 0.82 124036
macro avg 0.51 0.54 0.48 124036
weighted avg 0.95 0.82 0.88 124036
Accuracy: 0.8249137347221774
90-100%
precision recall f1-score support
0 0.03 0.23 0.06 2328
1 0.98 0.84 0.90 97067
accuracy 0.83 99395
macro avg 0.51 0.53 0.48 99395
weighted avg 0.96 0.83 0.88 99395
Accuracy: 0.8263393530861713
Treshold: 0.8
All
precision recall f1-score support
0 0.58 0.98 0.73 26119367
1 0.85 0.15 0.26 21615229
accuracy 0.60 47734596
macro avg 0.72 0.56 0.49 47734596
weighted avg 0.70 0.60 0.52 47734596
Accuracy: 0.6038039161366318
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.25 0.01 0.02 508421
accuracy 0.96 12561431
macro avg 0.60 0.50 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9588727590033334
1-10%
precision recall f1-score support
0 0.49 0.97 0.65 13368467
1 0.72 0.07 0.12 14466820
accuracy 0.50 27835287
macro avg 0.60 0.52 0.39 27835287
weighted avg 0.61 0.50 0.38 27835287
Accuracy: 0.501558687000425
10-20%
precision recall f1-score support
0 0.14 0.77 0.23 503365
1 0.89 0.27 0.41 3387274
accuracy 0.33 3890639
macro avg 0.51 0.52 0.32 3890639
weighted avg 0.79 0.33 0.39 3890639
Accuracy: 0.33381920039356006
20-40%
precision recall f1-score support
0 0.07 0.63 0.13 147488
1 0.94 0.41 0.57 1970425
accuracy 0.43 2117913
macro avg 0.51 0.52 0.35 2117913
weighted avg 0.88 0.43 0.54 2117913
Accuracy: 0.4275987729429868
40-80%
precision recall f1-score support
0 0.04 0.59 0.08 41616
1 0.97 0.46 0.62 1064279
accuracy 0.46 1105895
macro avg 0.50 0.52 0.35 1105895
weighted avg 0.93 0.46 0.60 1105895
Accuracy: 0.4609424945406209
80-90%
precision recall f1-score support
0 0.03 0.60 0.05 3093
1 0.98 0.46 0.62 120943
accuracy 0.46 124036
macro avg 0.50 0.53 0.34 124036
weighted avg 0.95 0.46 0.61 124036
Accuracy: 0.45997936083072655
90-100%
precision recall f1-score support
0 0.02 0.57 0.05 2328
1 0.98 0.45 0.62 97067
accuracy 0.46 99395
macro avg 0.50 0.51 0.33 99395
weighted avg 0.96 0.46 0.61 99395
Accuracy: 0.4557271492529805
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.00 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.27 0.50 0.35 47734596
weighted avg 0.30 0.55 0.39 47734596
Accuracy: 0.5471723275923399
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.00 0.00 0.00 508421
accuracy 0.96 12561431
macro avg 0.48 0.50 0.49 12561431
weighted avg 0.92 0.96 0.94 12561431
Accuracy: 0.95949999645741
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.00 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.24 0.50 0.32 27835287
weighted avg 0.23 0.48 0.31 27835287
Accuracy: 0.4802704926304514
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.00 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.06 0.50 0.11 3890639
weighted avg 0.02 0.13 0.03 3890639
Accuracy: 0.12937849026856513
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.00 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.03 0.50 0.07 2117913
weighted avg 0.00 0.07 0.01 2117913
Accuracy: 0.0696383656930195
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 0.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.02 0.50 0.04 1105895
weighted avg 0.00 0.04 0.00 1105895
Accuracy: 0.03763105900650604
80-90%
precision recall f1-score support
0 0.02 1.00 0.05 3093
1 0.00 0.00 0.00 120943
accuracy 0.02 124036
macro avg 0.01 0.50 0.02 124036
weighted avg 0.00 0.02 0.00 124036
Accuracy: 0.024936308813570254
90-100%
precision recall f1-score support
0 0.02 1.00 0.05 2328
1 0.00 0.00 0.00 97067
accuracy 0.02 99395
macro avg 0.01 0.50 0.02 99395
weighted avg 0.00 0.02 0.00 99395
Accuracy: 0.023421701292821572
0.2
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.48 0.63 24893266
1 0.60 0.95 0.74 20563095
accuracy 0.69 45456361
macro avg 0.76 0.71 0.68 45456361
weighted avg 0.77 0.69 0.68 45456361
Accuracy: 0.6928762951350197
0-1%
precision recall f1-score support
0 1.00 0.95 0.98 4873589
1 0.00 0.18 0.01 3872
accuracy 0.95 4877461
macro avg 0.50 0.56 0.49 4877461
weighted avg 1.00 0.95 0.97 4877461
Accuracy: 0.9516461536032784
1-10%
precision recall f1-score support
0 0.88 0.43 0.58 16949103
1 0.42 0.88 0.57 8016772
accuracy 0.57 24965875
macro avg 0.65 0.66 0.57 24965875
weighted avg 0.73 0.57 0.58 24965875
Accuracy: 0.574837413068839
10-20%
precision recall f1-score support
0 0.45 0.03 0.05 2057494
1 0.73 0.99 0.84 5461156
accuracy 0.72 7518650
macro avg 0.59 0.51 0.44 7518650
weighted avg 0.65 0.72 0.62 7518650
Accuracy: 0.7249309383998457
20-40%
precision recall f1-score support
0 0.32 0.02 0.04 744974
1 0.85 0.99 0.91 4060539
accuracy 0.84 4805513
macro avg 0.58 0.51 0.48 4805513
weighted avg 0.76 0.84 0.78 4805513
Accuracy: 0.8415238914138824
40-80%
precision recall f1-score support
0 0.26 0.02 0.04 235909
1 0.91 0.99 0.95 2483775
accuracy 0.91 2719684
macro avg 0.59 0.51 0.50 2719684
weighted avg 0.86 0.91 0.87 2719684
Accuracy: 0.9094703649394562
80-90%
precision recall f1-score support
0 0.23 0.03 0.05 18577
1 0.94 0.99 0.97 296772
accuracy 0.94 315349
macro avg 0.59 0.51 0.51 315349
weighted avg 0.90 0.94 0.91 315349
Accuracy: 0.9372821857687832
90-100%
precision recall f1-score support
0 0.22 0.03 0.05 13620
1 0.95 0.99 0.97 240209
accuracy 0.94 253829
macro avg 0.58 0.51 0.51 253829
weighted avg 0.91 0.94 0.92 253829
Accuracy: 0.9423667114474705
Treshold: 0.5
All
precision recall f1-score support
0 0.83 0.65 0.73 24893266
1 0.66 0.85 0.74 20563095
accuracy 0.74 45456361
macro avg 0.75 0.75 0.74 45456361
weighted avg 0.76 0.74 0.74 45456361
Accuracy: 0.7366780416056622
precision recall f1-score support
0 0.83 0.65 0.73 24893266
1 0.66 0.85 0.74 20563095
accuracy 0.74 45456361
macro avg 0.75 0.75 0.74 45456361
weighted avg 0.76 0.74 0.74 45456361
Accuracy: 0.7366780416056622
0-1%
precision recall f1-score support
0 1.00 0.98 0.99 4873589
1 0.01 0.11 0.01 3872
accuracy 0.98 4877461
macro avg 0.50 0.55 0.50 4877461
weighted avg 1.00 0.98 0.99 4877461
Accuracy: 0.9834707033023944
precision recall f1-score support
0 1.00 0.98 0.99 4873589
1 0.01 0.11 0.01 3872
accuracy 0.98 4877461
macro avg 0.50 0.55 0.50 4877461
weighted avg 1.00 0.98 0.99 4877461
Accuracy: 0.9834707033023944
1-10%
precision recall f1-score support
0 0.81 0.65 0.72 16949103
1 0.48 0.69 0.56 8016772
accuracy 0.66 24965875
macro avg 0.65 0.67 0.64 24965875
weighted avg 0.71 0.66 0.67 24965875
Accuracy: 0.6595340239426818
precision recall f1-score support
0 0.86 0.72 0.79 21822692
1 0.48 0.69 0.56 8020644
accuracy 0.71 29843336
macro avg 0.67 0.70 0.67 29843336
weighted avg 0.76 0.71 0.73 29843336
Accuracy: 0.7124767820862923
10-20%
precision recall f1-score support
0 0.85 0.67 0.75 23880186
1 0.57 0.79 0.66 13481800
accuracy 0.71 37361986
macro avg 0.71 0.73 0.71 37361986
weighted avg 0.75 0.71 0.72 37361986
Accuracy: 0.712518065822304
precision recall f1-score support
0 0.42 0.13 0.19 2057494
1 0.74 0.93 0.83 5461156
accuracy 0.71 7518650
macro avg 0.58 0.53 0.51 7518650
weighted avg 0.65 0.71 0.65 7518650
Accuracy: 0.7126819309317497
20-40%
precision recall f1-score support
0 0.84 0.65 0.73 24625160
1 0.63 0.83 0.71 17542339
accuracy 0.72 42167499
macro avg 0.73 0.74 0.72 42167499
weighted avg 0.75 0.72 0.73 42167499
Accuracy: 0.7247401606625994
precision recall f1-score support
0 0.25 0.08 0.13 744974
1 0.85 0.95 0.90 4060539
accuracy 0.82 4805513
macro avg 0.55 0.52 0.51 4805513
weighted avg 0.76 0.82 0.78 4805513
Accuracy: 0.8197647160667342
40-80%
precision recall f1-score support
0 0.16 0.08 0.10 235909
1 0.92 0.96 0.94 2483775
accuracy 0.88 2719684
macro avg 0.54 0.52 0.52 2719684
weighted avg 0.85 0.88 0.87 2719684
Accuracy: 0.8847226368945804
precision recall f1-score support
0 0.84 0.65 0.73 24861069
1 0.66 0.84 0.74 20026114
accuracy 0.73 44887183
macro avg 0.75 0.74 0.73 44887183
weighted avg 0.76 0.73 0.73 44887183
Accuracy: 0.7344333904847626
80-90%
precision recall f1-score support
0 0.12 0.08 0.09 18577
1 0.94 0.96 0.95 296772
accuracy 0.91 315349
macro avg 0.53 0.52 0.52 315349
weighted avg 0.89 0.91 0.90 315349
Accuracy: 0.9116280692185483
90-100%
precision recall f1-score support
0 0.10 0.07 0.09 13620
1 0.95 0.96 0.96 240209
accuracy 0.92 253829
macro avg 0.53 0.52 0.52 253829
weighted avg 0.90 0.92 0.91 253829
Accuracy: 0.9162704025150791
Treshold: 0.6
All
precision recall f1-score support
0 0.78 0.75 0.76 24893266
1 0.71 0.74 0.72 20563095
accuracy 0.74 45456361
macro avg 0.74 0.74 0.74 45456361
weighted avg 0.74 0.74 0.74 45456361
Accuracy: 0.7428696503004277
0-1%
precision recall f1-score support
0 1.00 0.99 1.00 4873589
1 0.01 0.07 0.02 3872
accuracy 0.99 4877461
macro avg 0.50 0.53 0.51 4877461
weighted avg 1.00 0.99 1.00 4877461
Accuracy: 0.9929291079928676
1-10%
precision recall f1-score support
0 0.77 0.77 0.77 16949103
1 0.51 0.52 0.52 8016772
accuracy 0.69 24965875
macro avg 0.64 0.64 0.64 24965875
weighted avg 0.69 0.69 0.69 24965875
Accuracy: 0.6879438032914929
10-20%
precision recall f1-score support
0 0.40 0.26 0.32 2057494
1 0.75 0.85 0.80 5461156
accuracy 0.69 7518650
macro avg 0.57 0.56 0.56 7518650
weighted avg 0.66 0.69 0.67 7518650
Accuracy: 0.6884778517420016
20-40%
precision recall f1-score support
0 0.24 0.18 0.20 744974
1 0.86 0.90 0.88 4060539
accuracy 0.79 4805513
macro avg 0.55 0.54 0.54 4805513
weighted avg 0.76 0.79 0.77 4805513
Accuracy: 0.7854501694199975
40-80%
precision recall f1-score support
0 0.14 0.15 0.15 235909
1 0.92 0.91 0.92 2483775
accuracy 0.85 2719684
macro avg 0.53 0.53 0.53 2719684
weighted avg 0.85 0.85 0.85 2719684
Accuracy: 0.8462534617992384
80-90%
precision recall f1-score support
0 0.10 0.15 0.12 18577
1 0.94 0.92 0.93 296772
accuracy 0.87 315349
macro avg 0.52 0.53 0.52 315349
weighted avg 0.90 0.87 0.88 315349
Accuracy: 0.8718816295596308
90-100%
precision recall f1-score support
0 0.09 0.14 0.11 13620
1 0.95 0.92 0.93 240209
accuracy 0.88 253829
macro avg 0.52 0.53 0.52 253829
weighted avg 0.90 0.88 0.89 253829
Accuracy: 0.8771850340189655
Treshold: 0.7
All
precision recall f1-score support
0 0.70 0.86 0.77 24893266
1 0.76 0.54 0.63 20563095
accuracy 0.72 45456361
macro avg 0.73 0.70 0.70 45456361
weighted avg 0.73 0.72 0.71 45456361
Accuracy: 0.7165491095954646
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.02 0.03 0.03 3872
accuracy 1.00 4877461
macro avg 0.51 0.52 0.51 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9978880405194424
1-10%
precision recall f1-score support
0 0.73 0.89 0.80 16949103
1 0.56 0.29 0.38 8016772
accuracy 0.70 24965875
macro avg 0.64 0.59 0.59 24965875
weighted avg 0.67 0.70 0.67 24965875
Accuracy: 0.6978752397021935
10-20%
precision recall f1-score support
0 0.34 0.52 0.41 2057494
1 0.78 0.63 0.69 5461156
accuracy 0.60 7518650
macro avg 0.56 0.57 0.55 7518650
weighted avg 0.66 0.60 0.62 7518650
Accuracy: 0.5972331469080221
20-40%
precision recall f1-score support
0 0.22 0.38 0.28 744974
1 0.87 0.75 0.80 4060539
accuracy 0.69 4805513
macro avg 0.54 0.56 0.54 4805513
weighted avg 0.77 0.69 0.72 4805513
Accuracy: 0.6909695177185037
40-80%
precision recall f1-score support
0 0.13 0.33 0.19 235909
1 0.93 0.79 0.85 2483775
accuracy 0.75 2719684
macro avg 0.53 0.56 0.52 2719684
weighted avg 0.86 0.75 0.79 2719684
Accuracy: 0.7465668805640655
80-90%
precision recall f1-score support
0 0.09 0.31 0.14 18577
1 0.95 0.80 0.87 296772
accuracy 0.77 315349
macro avg 0.52 0.56 0.50 315349
weighted avg 0.90 0.77 0.82 315349
Accuracy: 0.7704860329349388
90-100%
precision recall f1-score support
0 0.08 0.31 0.13 13620
1 0.95 0.80 0.87 240209
accuracy 0.78 253829
macro avg 0.52 0.56 0.50 253829
weighted avg 0.91 0.78 0.83 253829
Accuracy: 0.7770625105878367
Treshold: 0.8
All
precision recall f1-score support
0 0.59 0.97 0.73 24893266
1 0.83 0.17 0.28 20563095
accuracy 0.61 45456361
macro avg 0.71 0.57 0.51 45456361
weighted avg 0.69 0.61 0.53 45456361
Accuracy: 0.6077220083675418
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.00 0.01 3872
accuracy 1.00 4877461
macro avg 0.52 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991612439340878
1-10%
precision recall f1-score support
0 0.69 0.98 0.81 16949103
1 0.62 0.06 0.11 8016772
accuracy 0.69 24965875
macro avg 0.65 0.52 0.46 24965875
weighted avg 0.67 0.69 0.59 24965875
Accuracy: 0.6862760468038873
10-20%
precision recall f1-score support
0 0.28 0.90 0.43 2057494
1 0.79 0.15 0.25 5461156
accuracy 0.35 7518650
macro avg 0.54 0.52 0.34 7518650
weighted avg 0.66 0.35 0.30 7518650
Accuracy: 0.3530327917910795
20-40%
precision recall f1-score support
0 0.17 0.81 0.28 744974
1 0.88 0.26 0.40 4060539
accuracy 0.34 4805513
macro avg 0.52 0.53 0.34 4805513
weighted avg 0.77 0.34 0.38 4805513
Accuracy: 0.3438069983371182
40-80%
precision recall f1-score support
0 0.10 0.72 0.17 235909
1 0.93 0.36 0.52 2483775
accuracy 0.39 2719684
macro avg 0.51 0.54 0.35 2719684
weighted avg 0.86 0.39 0.49 2719684
Accuracy: 0.39309125619005736
80-90%
precision recall f1-score support
0 0.07 0.68 0.12 18577
1 0.95 0.41 0.57 296772
accuracy 0.42 315349
macro avg 0.51 0.54 0.35 315349
weighted avg 0.90 0.42 0.54 315349
Accuracy: 0.42294410319994674
90-100%
precision recall f1-score support
0 0.06 0.67 0.11 13620
1 0.96 0.42 0.58 240209
accuracy 0.43 253829
macro avg 0.51 0.54 0.35 253829
weighted avg 0.91 0.43 0.55 253829
Accuracy: 0.4295056908391082
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.00 0.00 0.00 20563095
accuracy 0.55 45456361
macro avg 0.27 0.50 0.35 45456361
weighted avg 0.30 0.55 0.39 45456361
Accuracy: 0.5476299785633962
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.00 0.00 0.00 3872
accuracy 1.00 4877461
macro avg 0.50 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9992061443443627
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.00 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.34 0.50 0.40 24965875
weighted avg 0.46 0.68 0.55 24965875
Accuracy: 0.678890805950122
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.00 0.00 0.00 5461156
accuracy 0.27 7518650
macro avg 0.14 0.50 0.21 7518650
weighted avg 0.07 0.27 0.12 7518650
Accuracy: 0.2736520518976146
20-40%
precision recall f1-score support
0 0.16 1.00 0.27 744974
1 0.00 0.00 0.00 4060539
accuracy 0.16 4805513
macro avg 0.08 0.50 0.13 4805513
weighted avg 0.02 0.16 0.04 4805513
Accuracy: 0.15502486415082012
40-80%
precision recall f1-score support
0 0.09 1.00 0.16 235909
1 0.00 0.00 0.00 2483775
accuracy 0.09 2719684
macro avg 0.04 0.50 0.08 2719684
weighted avg 0.01 0.09 0.01 2719684
Accuracy: 0.08674132730126
80-90%
precision recall f1-score support
0 0.06 1.00 0.11 18577
1 0.00 0.00 0.00 296772
accuracy 0.06 315349
macro avg 0.03 0.50 0.06 315349
weighted avg 0.00 0.06 0.01 315349
Accuracy: 0.05890933537128705
90-100%
precision recall f1-score support
0 0.05 1.00 0.10 13620
1 0.00 0.00 0.00 240209
accuracy 0.05 253829
macro avg 0.03 0.50 0.05 253829
weighted avg 0.00 0.05 0.01 253829
Accuracy: 0.05365817144613105
0.4
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.50 0.64 22531902
1 0.58 0.95 0.72 16938696
accuracy 0.69 39470598
macro avg 0.75 0.72 0.68 39470598
weighted avg 0.78 0.69 0.68 39470598
Accuracy: 0.6886409980411242
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999606451359001
1-10%
precision recall f1-score support
0 0.95 0.74 0.83 11439888
1 0.22 0.67 0.33 1271288
accuracy 0.73 12711176
macro avg 0.59 0.70 0.58 12711176
weighted avg 0.88 0.73 0.78 12711176
Accuracy: 0.7289276775020659
10-20%
precision recall f1-score support
0 0.78 0.19 0.30 5044441
1 0.46 0.93 0.62 3812372
accuracy 0.51 8856813
macro avg 0.62 0.56 0.46 8856813
weighted avg 0.65 0.51 0.44 8856813
Accuracy: 0.5069134913427663
20-40%
precision recall f1-score support
0 0.59 0.06 0.12 2995598
1 0.66 0.98 0.79 5583215
accuracy 0.66 8578813
macro avg 0.62 0.52 0.45 8578813
weighted avg 0.63 0.66 0.55 8578813
Accuracy: 0.6575001693124678
40-80%
precision recall f1-score support
0 0.41 0.05 0.08 1295061
1 0.80 0.98 0.88 5001564
accuracy 0.79 6296625
macro avg 0.60 0.51 0.48 6296625
weighted avg 0.72 0.79 0.72 6296625
Accuracy: 0.7901185158715979
80-90%
precision recall f1-score support
0 0.33 0.05 0.08 117971
1 0.86 0.98 0.92 692761
accuracy 0.85 810732
macro avg 0.60 0.51 0.50 810732
weighted avg 0.78 0.85 0.80 810732
Accuracy: 0.8478683461365778
90-100%
precision recall f1-score support
0 0.32 0.05 0.08 88944
1 0.87 0.98 0.92 577496
accuracy 0.86 666440
macro avg 0.60 0.52 0.50 666440
weighted avg 0.80 0.86 0.81 666440
Accuracy: 0.859676790108637
Treshold: 0.5
All
precision recall f1-score support
0 0.85 0.66 0.74 22531902
1 0.65 0.84 0.73 16938696
accuracy 0.74 39470598
macro avg 0.75 0.75 0.74 39470598
weighted avg 0.76 0.74 0.74 39470598
Accuracy: 0.7380616072753698
precision recall f1-score support
0 0.85 0.66 0.74 22531902
1 0.65 0.84 0.73 16938696
accuracy 0.74 39470598
macro avg 0.75 0.75 0.74 39470598
weighted avg 0.76 0.74 0.74 39470598
Accuracy: 0.738061632610684
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999987096765869
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999987096765869
1-10%
precision recall f1-score support
0 0.94 0.89 0.91 12989887
1 0.27 0.42 0.33 1271288
accuracy 0.85 14261175
macro avg 0.61 0.65 0.62 14261175
weighted avg 0.88 0.85 0.86 14261175
Accuracy: 0.848070232642121
precision recall f1-score support
0 0.93 0.88 0.90 11439888
1 0.27 0.42 0.33 1271288
accuracy 0.83 12711176
macro avg 0.60 0.65 0.62 12711176
weighted avg 0.87 0.83 0.85 12711176
Accuracy: 0.829544095683987
10-20%
precision recall f1-score support
0 0.89 0.77 0.83 18034328
1 0.46 0.68 0.54 5083660
accuracy 0.75 23117988
macro avg 0.68 0.72 0.69 23117988
weighted avg 0.80 0.75 0.77 23117988
Accuracy: 0.751271780225857
precision recall f1-score support
0 0.72 0.47 0.57 5044441
1 0.52 0.76 0.62 3812372
accuracy 0.60 8856813
macro avg 0.62 0.62 0.59 8856813
weighted avg 0.64 0.60 0.59 8856813
Accuracy: 0.5954075128378571
20-40%
precision recall f1-score support
0 0.55 0.23 0.33 2995598
1 0.69 0.90 0.78 5583215
accuracy 0.67 8578813
macro avg 0.62 0.57 0.55 8578813
weighted avg 0.64 0.67 0.62 8578813
Accuracy: 0.6660275728122294
40-80%
precision recall f1-score support
0 0.85 0.66 0.75 22324987
1 0.64 0.83 0.72 15668439
accuracy 0.73 37993426
macro avg 0.74 0.75 0.73 37993426
weighted avg 0.76 0.73 0.74 37993426
Accuracy: 0.7347993834512317
precision recall f1-score support
0 0.36 0.17 0.23 1295061
1 0.81 0.92 0.86 5001564
accuracy 0.77 6296625
macro avg 0.59 0.55 0.55 6296625
weighted avg 0.72 0.77 0.73 6296625
Accuracy: 0.7680190578285987
80-90%
precision recall f1-score support
0 0.28 0.16 0.20 117971
1 0.87 0.93 0.90 692761
accuracy 0.82 810732
macro avg 0.57 0.54 0.55 810732
weighted avg 0.78 0.82 0.80 810732
Accuracy: 0.8174316543568034
90-100%
precision recall f1-score support
0 0.26 0.15 0.19 88944
1 0.88 0.93 0.90 577496
accuracy 0.83 666440
macro avg 0.57 0.54 0.55 666440
weighted avg 0.79 0.83 0.81 666440
Accuracy: 0.8274863453574215
Treshold: 0.6
All
precision recall f1-score support
0 0.79 0.76 0.77 22531902
1 0.69 0.74 0.72 16938696
accuracy 0.75 39470598
macro avg 0.74 0.75 0.74 39470598
weighted avg 0.75 0.75 0.75 39470598
Accuracy: 0.7480667761861627
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999993548382935
1-10%
precision recall f1-score support
0 0.92 0.93 0.92 11439888
1 0.31 0.30 0.30 1271288
accuracy 0.86 12711176
macro avg 0.62 0.61 0.61 12711176
weighted avg 0.86 0.86 0.86 12711176
Accuracy: 0.8637388074872066
10-20%
precision recall f1-score support
0 0.68 0.64 0.66 5044441
1 0.56 0.60 0.58 3812372
accuracy 0.63 8856813
macro avg 0.62 0.62 0.62 8856813
weighted avg 0.63 0.63 0.63 8856813
Accuracy: 0.6256980925305751
20-40%
precision recall f1-score support
0 0.52 0.40 0.45 2995598
1 0.71 0.80 0.76 5583215
accuracy 0.66 8578813
macro avg 0.62 0.60 0.60 8578813
weighted avg 0.65 0.66 0.65 8578813
Accuracy: 0.6613833405623831
40-80%
precision recall f1-score support
0 0.34 0.30 0.32 1295061
1 0.82 0.85 0.84 5001564
accuracy 0.74 6296625
macro avg 0.58 0.57 0.58 6296625
weighted avg 0.72 0.74 0.73 6296625
Accuracy: 0.7355556349631747
80-90%
precision recall f1-score support
0 0.25 0.28 0.27 117971
1 0.88 0.86 0.87 692761
accuracy 0.77 810732
macro avg 0.56 0.57 0.57 810732
weighted avg 0.78 0.77 0.78 810732
Accuracy: 0.774581489320762
90-100%
precision recall f1-score support
0 0.24 0.27 0.25 88944
1 0.89 0.86 0.87 577496
accuracy 0.78 666440
macro avg 0.56 0.57 0.56 666440
weighted avg 0.80 0.78 0.79 666440
Accuracy: 0.7839235340015606
Treshold: 0.7
All
precision recall f1-score support
0 0.72 0.86 0.78 22531902
1 0.75 0.55 0.64 16938696
accuracy 0.73 39470598
macro avg 0.74 0.71 0.71 39470598
weighted avg 0.73 0.73 0.72 39470598
Accuracy: 0.7295214782405881
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.91 0.97 0.94 11439888
1 0.37 0.17 0.24 1271288
accuracy 0.89 12711176
macro avg 0.64 0.57 0.59 12711176
weighted avg 0.86 0.89 0.87 12711176
Accuracy: 0.8877049613662812
10-20%
precision recall f1-score support
0 0.64 0.82 0.71 5044441
1 0.61 0.38 0.47 3812372
accuracy 0.63 8856813
macro avg 0.62 0.60 0.59 8856813
weighted avg 0.62 0.63 0.61 8856813
Accuracy: 0.6289794082815117
20-40%
precision recall f1-score support
0 0.46 0.64 0.54 2995598
1 0.76 0.60 0.67 5583215
accuracy 0.62 8578813
macro avg 0.61 0.62 0.60 8578813
weighted avg 0.65 0.62 0.62 8578813
Accuracy: 0.6154488971842608
40-80%
precision recall f1-score support
0 0.30 0.53 0.39 1295061
1 0.85 0.68 0.76 5001564
accuracy 0.65 6296625
macro avg 0.58 0.61 0.57 6296625
weighted avg 0.74 0.65 0.68 6296625
Accuracy: 0.6527049014352927
80-90%
precision recall f1-score support
0 0.22 0.50 0.31 117971
1 0.89 0.70 0.79 692761
accuracy 0.67 810732
macro avg 0.56 0.60 0.55 810732
weighted avg 0.79 0.67 0.72 810732
Accuracy: 0.6739526748666637
90-100%
precision recall f1-score support
0 0.21 0.49 0.29 88944
1 0.90 0.71 0.79 577496
accuracy 0.68 666440
macro avg 0.55 0.60 0.54 666440
weighted avg 0.81 0.68 0.73 666440
Accuracy: 0.6813351539523438
Treshold: 0.8
All
precision recall f1-score support
0 0.62 0.96 0.76 22531902
1 0.82 0.23 0.36 16938696
accuracy 0.65 39470598
macro avg 0.72 0.60 0.56 39470598
weighted avg 0.71 0.65 0.59 39470598
Accuracy: 0.6486970377291978
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 0.99 0.95 11439888
1 0.47 0.06 0.10 1271288
accuracy 0.90 12711176
macro avg 0.69 0.52 0.52 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.8992394566796966
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.13 0.22 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.48 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5995312309292293
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.81 0.23 0.36 5583215
accuracy 0.47 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.66 0.47 0.43 8578813
Accuracy: 0.4669942100381486
40-80%
precision recall f1-score support
0 0.24 0.84 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.43 6296625
macro avg 0.56 0.58 0.42 6296625
weighted avg 0.75 0.43 0.45 6296625
Accuracy: 0.42776217418061263
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.42 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.42 0.47 810732
Accuracy: 0.41582668502045067
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.36 0.51 577496
accuracy 0.42 666440
macro avg 0.54 0.58 0.39 666440
weighted avg 0.82 0.42 0.48 666440
Accuracy: 0.41608546905948024
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.00 0.00 0.00 16938696
accuracy 0.57 39470598
macro avg 0.29 0.50 0.36 39470598
weighted avg 0.33 0.57 0.41 39470598
Accuracy: 0.5708528155565314
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 1.00 0.95 11439888
1 0.00 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.45 0.50 0.47 12711176
weighted avg 0.81 0.90 0.85 12711176
Accuracy: 0.8999865944740282
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.00 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.28 0.50 0.36 8856813
weighted avg 0.32 0.57 0.41 8856813
Accuracy: 0.5695548726161431
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.00 0.00 0.00 5583215
accuracy 0.35 8578813
macro avg 0.17 0.50 0.26 8578813
weighted avg 0.12 0.35 0.18 8578813
Accuracy: 0.34918560411562766
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.00 0.00 0.00 5001564
accuracy 0.21 6296625
macro avg 0.10 0.50 0.17 6296625
weighted avg 0.04 0.21 0.07 6296625
Accuracy: 0.20567542135667918
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.00 0.00 0.00 692761
accuracy 0.15 810732
macro avg 0.07 0.50 0.13 810732
weighted avg 0.02 0.15 0.04 810732
Accuracy: 0.14551171040491803
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.00 0.00 0.00 577496
accuracy 0.13 666440
macro avg 0.07 0.50 0.12 666440
weighted avg 0.02 0.13 0.03 666440
Accuracy: 0.13346137686813517
LR_8
0.01
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.47 0.62 28055468
1 0.58 0.95 0.72 21729815
accuracy 0.68 49785283
macro avg 0.75 0.71 0.67 49785283
weighted avg 0.77 0.68 0.66 49785283
Accuracy: 0.6754580063349244
0-1%
precision recall f1-score support
0 0.92 0.47 0.62 27764588
1 0.52 0.93 0.67 17098553
accuracy 0.65 44863141
macro avg 0.72 0.70 0.64 44863141
weighted avg 0.77 0.65 0.64 44863141
Accuracy: 0.6463347272095817
1-10%
precision recall f1-score support
0 0.00 0.00 0.00 287564
1 0.94 1.00 0.97 4164787
accuracy 0.94 4452351
macro avg 0.47 0.50 0.48 4452351
weighted avg 0.87 0.94 0.90 4452351
Accuracy: 0.9354129986607076
10-20%
precision recall f1-score support
0 0.00 0.00 0.00 2455
1 0.99 1.00 1.00 257616
accuracy 0.99 260071
macro avg 0.50 0.50 0.50 260071
weighted avg 0.98 0.99 0.99 260071
Accuracy: 0.9905602700800935
20-40%
precision recall f1-score support
0 0.00 0.00 0.00 659
1 0.99 1.00 1.00 130568
accuracy 0.99 131227
macro avg 0.50 0.50 0.50 131227
weighted avg 0.99 0.99 0.99 131227
Accuracy: 0.9949781676027037
40-80%
precision recall f1-score support
0 0.00 0.00 0.00 169
1 1.00 1.00 1.00 65234
accuracy 1.00 65403
macro avg 0.50 0.50 0.50 65403
weighted avg 0.99 1.00 1.00 65403
Accuracy: 0.9974160206718347
80-90%
precision recall f1-score support
0 0.00 0.00 0.00 15
1 1.00 1.00 1.00 7371
accuracy 1.00 7386
macro avg 0.50 0.50 0.50 7386
weighted avg 1.00 1.00 1.00 7386
Accuracy: 0.9979691307879772
90-100%
precision recall f1-score support
0 0.00 0.00 0.00 18
1 1.00 1.00 1.00 5686
accuracy 1.00 5704
macro avg 0.50 0.50 0.50 5704
weighted avg 0.99 1.00 1.00 5704
Accuracy: 0.9968443197755961
Treshold: 0.5
All
precision recall f1-score support
0 0.84 0.64 0.72 28055468
1 0.64 0.84 0.73 21729815
accuracy 0.73 49785283
macro avg 0.74 0.74 0.73 49785283
weighted avg 0.75 0.73 0.73 49785283
Accuracy: 0.7256453880155708
precision recall f1-score support
0 0.84 0.64 0.72 28055468
1 0.64 0.84 0.73 21729815
accuracy 0.73 49785283
macro avg 0.74 0.74 0.73 49785283
weighted avg 0.75 0.73 0.73 49785283
Accuracy: 0.7256452875842847
0-1%
precision recall f1-score support
0 0.84 0.65 0.73 27764588
1 0.58 0.80 0.67 17098553
accuracy 0.70 44863141
macro avg 0.71 0.72 0.70 44863141
weighted avg 0.74 0.70 0.71 44863141
Accuracy: 0.70273686365384
precision recall f1-score support
0 0.84 0.65 0.73 27764588
1 0.58 0.80 0.67 17098553
accuracy 0.70 44863141
macro avg 0.71 0.72 0.70 44863141
weighted avg 0.74 0.70 0.71 44863141
Accuracy: 0.7027367522037746
1-10%
precision recall f1-score support
0 0.10 0.01 0.02 287564
1 0.94 0.99 0.96 4164787
accuracy 0.93 4452351
macro avg 0.52 0.50 0.49 4452351
weighted avg 0.88 0.93 0.90 4452351
Accuracy: 0.9287387719431823
precision recall f1-score support
0 0.84 0.64 0.72 28052152
1 0.64 0.83 0.72 21263340
accuracy 0.72 49315492
macro avg 0.74 0.74 0.72 49315492
weighted avg 0.75 0.72 0.72 49315492
Accuracy: 0.723140995936936
10-20%
precision recall f1-score support
0 0.84 0.64 0.72 28054607
1 0.64 0.84 0.73 21520956
accuracy 0.72 49575563
macro avg 0.74 0.74 0.72 49575563
weighted avg 0.75 0.72 0.72 49575563
Accuracy: 0.7245276266454099
precision recall f1-score support
0 0.04 0.01 0.02 2455
1 0.99 1.00 0.99 257616
accuracy 0.99 260071
macro avg 0.51 0.50 0.51 260071
weighted avg 0.98 0.99 0.98 260071
Accuracy: 0.987464961491285
20-40%
precision recall f1-score support
0 0.84 0.64 0.72 28055266
1 0.64 0.84 0.73 21651524
accuracy 0.73 49706790
macro avg 0.74 0.74 0.73 49706790
weighted avg 0.75 0.73 0.73 49706790
Accuracy: 0.7252297321955411
precision recall f1-score support
0 0.02 0.02 0.02 659
1 1.00 1.00 1.00 130568
accuracy 0.99 131227
macro avg 0.51 0.51 0.51 131227
weighted avg 0.99 0.99 0.99 131227
Accuracy: 0.990474521249438
40-80%
precision recall f1-score support
0 0.84 0.64 0.72 28055435
1 0.64 0.84 0.73 21716758
accuracy 0.73 49772193
macro avg 0.74 0.74 0.73 49772193
weighted avg 0.75 0.73 0.73 49772193
Accuracy: 0.7255765885180104
precision recall f1-score support
0 0.02 0.07 0.03 169
1 1.00 0.99 0.99 65234
accuracy 0.99 65403
macro avg 0.51 0.53 0.51 65403
weighted avg 1.00 0.99 0.99 65403
Accuracy: 0.989190098313533
80-90%
precision recall f1-score support
0 0.01 0.07 0.02 15
1 1.00 0.99 0.99 7371
accuracy 0.99 7386
macro avg 0.51 0.53 0.51 7386
weighted avg 1.00 0.99 0.99 7386
Accuracy: 0.9883563498510696
90-100%
precision recall f1-score support
0 0.06 0.22 0.09 18
1 1.00 0.99 0.99 5686
accuracy 0.99 5704
macro avg 0.53 0.61 0.54 5704
weighted avg 0.99 0.99 0.99 5704
Accuracy: 0.9857994389901823
Treshold: 0.6
All
precision recall f1-score support
0 0.77 0.75 0.76 28055468
1 0.69 0.72 0.70 21729815
accuracy 0.74 49785283
macro avg 0.73 0.73 0.73 49785283
weighted avg 0.74 0.74 0.74 49785283
Accuracy: 0.7356635293205022
0-1%
precision recall f1-score support
0 0.78 0.76 0.77 27764588
1 0.62 0.65 0.64 17098553
accuracy 0.72 44863141
macro avg 0.70 0.70 0.70 44863141
weighted avg 0.72 0.72 0.72 44863141
Accuracy: 0.7159833726309979
1-10%
precision recall f1-score support
0 0.09 0.05 0.06 287564
1 0.94 0.97 0.95 4164787
accuracy 0.91 4452351
macro avg 0.51 0.51 0.51 4452351
weighted avg 0.88 0.91 0.89 4452351
Accuracy: 0.9088562424660589
10-20%
precision recall f1-score support
0 0.02 0.03 0.02 2455
1 0.99 0.99 0.99 257616
accuracy 0.98 260071
macro avg 0.50 0.51 0.51 260071
weighted avg 0.98 0.98 0.98 260071
Accuracy: 0.9763910624406412
20-40%
precision recall f1-score support
0 0.01 0.06 0.02 659
1 1.00 0.98 0.99 130568
accuracy 0.97 131227
macro avg 0.50 0.52 0.50 131227
weighted avg 0.99 0.97 0.98 131227
Accuracy: 0.9748451157155159
40-80%
precision recall f1-score support
0 0.01 0.11 0.02 169
1 1.00 0.97 0.98 65234
accuracy 0.96 65403
macro avg 0.50 0.54 0.50 65403
weighted avg 1.00 0.96 0.98 65403
Accuracy: 0.9641759552314114
80-90%
precision recall f1-score support
0 0.01 0.13 0.01 15
1 1.00 0.96 0.98 7371
accuracy 0.96 7386
macro avg 0.50 0.55 0.50 7386
weighted avg 1.00 0.96 0.98 7386
Accuracy: 0.9568101814243163
90-100%
precision recall f1-score support
0 0.01 0.22 0.03 18
1 1.00 0.95 0.97 5686
accuracy 0.95 5704
macro avg 0.51 0.59 0.50 5704
weighted avg 0.99 0.95 0.97 5704
Accuracy: 0.9507363253856943
Treshold: 0.7
All
precision recall f1-score support
0 0.69 0.88 0.77 28055468
1 0.76 0.50 0.60 21729815
accuracy 0.71 49785283
macro avg 0.73 0.69 0.69 49785283
weighted avg 0.72 0.71 0.70 49785283
Accuracy: 0.7116202794307708
0-1%
precision recall f1-score support
0 0.70 0.88 0.78 27764588
1 0.68 0.39 0.50 17098553
accuracy 0.70 44863141
macro avg 0.69 0.64 0.64 44863141
weighted avg 0.69 0.70 0.67 44863141
Accuracy: 0.6969017394479803
1-10%
precision recall f1-score support
0 0.08 0.15 0.11 287564
1 0.94 0.89 0.91 4164787
accuracy 0.84 4452351
macro avg 0.51 0.52 0.51 4452351
weighted avg 0.88 0.84 0.86 4452351
Accuracy: 0.8377809835747451
10-20%
precision recall f1-score support
0 0.01 0.07 0.02 2455
1 0.99 0.95 0.97 257616
accuracy 0.94 260071
macro avg 0.50 0.51 0.49 260071
weighted avg 0.98 0.94 0.96 260071
Accuracy: 0.9370979463300406
20-40%
precision recall f1-score support
0 0.01 0.12 0.01 659
1 1.00 0.92 0.96 130568
accuracy 0.92 131227
macro avg 0.50 0.52 0.49 131227
weighted avg 0.99 0.92 0.95 131227
Accuracy: 0.91796657700016
40-80%
precision recall f1-score support
0 0.00 0.18 0.01 169
1 1.00 0.88 0.94 65234
accuracy 0.88 65403
macro avg 0.50 0.53 0.47 65403
weighted avg 1.00 0.88 0.93 65403
Accuracy: 0.8798067366940354
80-90%
precision recall f1-score support
0 0.00 0.13 0.00 15
1 1.00 0.86 0.92 7371
accuracy 0.86 7386
macro avg 0.50 0.50 0.46 7386
weighted avg 1.00 0.86 0.92 7386
Accuracy: 0.8575683725968047
90-100%
precision recall f1-score support
0 0.01 0.33 0.01 18
1 1.00 0.86 0.92 5686
accuracy 0.85 5704
macro avg 0.50 0.59 0.47 5704
weighted avg 0.99 0.85 0.92 5704
Accuracy: 0.8539621318373072
Treshold: 0.8
All
precision recall f1-score support
0 0.60 0.99 0.75 28055468
1 0.90 0.15 0.26 21729815
accuracy 0.62 49785283
macro avg 0.75 0.57 0.50 49785283
weighted avg 0.73 0.62 0.53 49785283
Accuracy: 0.6226645532978089
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.78 0.05 0.09 17098553
accuracy 0.63 44863141
macro avg 0.71 0.52 0.43 44863141
weighted avg 0.69 0.63 0.51 44863141
Accuracy: 0.6318400443696085
1-10%
precision recall f1-score support
0 0.07 0.56 0.13 287564
1 0.94 0.52 0.67 4164787
accuracy 0.52 4452351
macro avg 0.51 0.54 0.40 4452351
weighted avg 0.89 0.52 0.64 4452351
Accuracy: 0.5229810048668669
10-20%
precision recall f1-score support
0 0.01 0.25 0.02 2455
1 0.99 0.76 0.86 257616
accuracy 0.76 260071
macro avg 0.50 0.51 0.44 260071
weighted avg 0.98 0.76 0.86 260071
Accuracy: 0.7600386048425237
20-40%
precision recall f1-score support
0 0.01 0.36 0.01 659
1 1.00 0.67 0.80 130568
accuracy 0.67 131227
macro avg 0.50 0.51 0.41 131227
weighted avg 0.99 0.67 0.80 131227
Accuracy: 0.6670807074763577
40-80%
precision recall f1-score support
0 0.00 0.50 0.01 169
1 1.00 0.52 0.68 65234
accuracy 0.52 65403
macro avg 0.50 0.51 0.34 65403
weighted avg 0.99 0.52 0.68 65403
Accuracy: 0.5198232496980261
80-90%
precision recall f1-score support
0 0.00 0.53 0.00 15
1 1.00 0.42 0.59 7371
accuracy 0.42 7386
macro avg 0.50 0.48 0.30 7386
weighted avg 1.00 0.42 0.59 7386
Accuracy: 0.4217438396967235
90-100%
precision recall f1-score support
0 0.00 0.56 0.01 18
1 1.00 0.42 0.59 5686
accuracy 0.42 5704
macro avg 0.50 0.49 0.30 5704
weighted avg 0.99 0.42 0.59 5704
Accuracy: 0.41917952314165496
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 28055468
1 0.95 0.03 0.06 21729815
accuracy 0.58 49785283
macro avg 0.76 0.51 0.39 49785283
weighted avg 0.74 0.58 0.44 49785283
Accuracy: 0.5763193713290733
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.56 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.59 0.50 0.38 44863141
weighted avg 0.60 0.62 0.47 44863141
Accuracy: 0.6189191256136078
1-10%
precision recall f1-score support
0 0.07 0.92 0.13 287564
1 0.96 0.14 0.24 4164787
accuracy 0.19 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.19 0.23 4452351
Accuracy: 0.18705465943722765
10-20%
precision recall f1-score support
0 0.01 0.69 0.02 2455
1 0.99 0.31 0.47 257616
accuracy 0.31 260071
macro avg 0.50 0.50 0.24 260071
weighted avg 0.98 0.31 0.46 260071
Accuracy: 0.3102037520523242
20-40%
precision recall f1-score support
0 0.00 0.90 0.01 659
1 0.99 0.09 0.16 130568
accuracy 0.09 131227
macro avg 0.50 0.49 0.08 131227
weighted avg 0.99 0.09 0.16 131227
Accuracy: 0.08940233336127473
40-80%
precision recall f1-score support
0 0.00 1.00 0.01 169
1 1.00 0.00 0.00 65234
accuracy 0.00 65403
macro avg 0.50 0.50 0.00 65403
weighted avg 1.00 0.00 0.00 65403
Accuracy: 0.00449520664189716
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 0.00 0.00 0.00 7371
accuracy 0.00 7386
macro avg 0.00 0.50 0.00 7386
weighted avg 0.00 0.00 0.00 7386
Accuracy: 0.0020308692120227455
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 0.00 0.00 0.00 5686
accuracy 0.00 5704
macro avg 0.00 0.50 0.00 5704
weighted avg 0.00 0.00 0.00 5704
Accuracy: 0.003155680224403927
0.1
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.48 0.63 26119367
1 0.60 0.95 0.73 21615229
accuracy 0.69 47734596
macro avg 0.76 0.71 0.68 47734596
weighted avg 0.77 0.69 0.68 47734596
Accuracy: 0.6900730656649948
0-1%
precision recall f1-score support
0 0.97 0.82 0.89 12053010
1 0.08 0.40 0.14 508421
accuracy 0.80 12561431
macro avg 0.53 0.61 0.51 12561431
weighted avg 0.93 0.80 0.86 12561431
Accuracy: 0.7982951942338417
1-10%
precision recall f1-score support
0 0.76 0.20 0.31 13368467
1 0.56 0.94 0.70 14466820
accuracy 0.59 27835287
macro avg 0.66 0.57 0.51 27835287
weighted avg 0.66 0.59 0.52 27835287
Accuracy: 0.5850971825797953
10-20%
precision recall f1-score support
0 0.28 0.01 0.02 503365
1 0.87 1.00 0.93 3387274
accuracy 0.87 3890639
macro avg 0.57 0.50 0.47 3890639
weighted avg 0.79 0.87 0.81 3890639
Accuracy: 0.8686557658009392
20-40%
precision recall f1-score support
0 0.24 0.01 0.02 147488
1 0.93 1.00 0.96 1970425
accuracy 0.93 2117913
macro avg 0.59 0.50 0.49 2117913
weighted avg 0.88 0.93 0.90 2117913
Accuracy: 0.9285985779396981
40-80%
precision recall f1-score support
0 0.22 0.02 0.03 41616
1 0.96 1.00 0.98 1064279
accuracy 0.96 1105895
macro avg 0.59 0.51 0.51 1105895
weighted avg 0.93 0.96 0.94 1105895
Accuracy: 0.9606002378164292
80-90%
precision recall f1-score support
0 0.23 0.03 0.05 3093
1 0.98 1.00 0.99 120943
accuracy 0.97 124036
macro avg 0.60 0.51 0.52 124036
weighted avg 0.96 0.97 0.96 124036
Accuracy: 0.9733948208584604
90-100%
precision recall f1-score support
0 0.22 0.03 0.05 2328
1 0.98 1.00 0.99 97067
accuracy 0.97 99395
macro avg 0.60 0.51 0.52 99395
weighted avg 0.96 0.97 0.97 99395
Accuracy: 0.9749484380502037
Treshold: 0.5
All
precision recall f1-score support
0 0.83 0.64 0.73 26119367
1 0.66 0.85 0.74 21615229
accuracy 0.73 47734596
macro avg 0.75 0.74 0.73 47734596
weighted avg 0.76 0.73 0.73 47734596
Accuracy: 0.7341861236240482
precision recall f1-score support
0 0.83 0.64 0.73 26119367
1 0.66 0.85 0.74 21615229
accuracy 0.73 47734596
macro avg 0.75 0.74 0.73 47734596
weighted avg 0.76 0.73 0.73 47734596
Accuracy: 0.7341861236240482
0-1%
precision recall f1-score support
0 0.97 0.91 0.94 12053010
1 0.10 0.23 0.14 508421
accuracy 0.88 12561431
macro avg 0.53 0.57 0.54 12561431
weighted avg 0.93 0.88 0.90 12561431
Accuracy: 0.8826342317208923
precision recall f1-score support
0 0.97 0.91 0.94 12053010
1 0.10 0.23 0.14 508421
accuracy 0.88 12561431
macro avg 0.53 0.57 0.54 12561431
weighted avg 0.93 0.88 0.90 12561431
Accuracy: 0.8826342317208923
1-10%
precision recall f1-score support
0 0.84 0.66 0.74 25421477
1 0.58 0.79 0.67 14975241
accuracy 0.71 40396718
macro avg 0.71 0.72 0.70 40396718
weighted avg 0.74 0.71 0.71 40396718
Accuracy: 0.7066991432323785
precision recall f1-score support
0 0.68 0.43 0.53 13368467
1 0.61 0.81 0.69 14466820
accuracy 0.63 27835287
macro avg 0.64 0.62 0.61 27835287
weighted avg 0.64 0.63 0.61 27835287
Accuracy: 0.6273036451896472
10-20%
precision recall f1-score support
0 0.84 0.65 0.73 25924842
1 0.62 0.82 0.71 18362515
accuracy 0.72 44287357
macro avg 0.73 0.73 0.72 44287357
weighted avg 0.75 0.72 0.72 44287357
Accuracy: 0.7194057437204934
precision recall f1-score support
0 0.20 0.05 0.08 503365
1 0.87 0.97 0.92 3387274
accuracy 0.85 3890639
macro avg 0.54 0.51 0.50 3890639
weighted avg 0.79 0.85 0.81 3890639
Accuracy: 0.8513390730931346
20-40%
precision recall f1-score support
0 0.84 0.64 0.73 26072330
1 0.65 0.84 0.73 20332940
accuracy 0.73 46405270
macro avg 0.74 0.74 0.73 46405270
weighted avg 0.75 0.73 0.73 46405270
Accuracy: 0.7281674904595965
precision recall f1-score support
0 0.12 0.04 0.06 147488
1 0.93 0.98 0.95 1970425
accuracy 0.91 2117913
macro avg 0.53 0.51 0.51 2117913
weighted avg 0.88 0.91 0.89 2117913
Accuracy: 0.9113830454792052
40-80%
precision recall f1-score support
0 0.83 0.64 0.73 26113946
1 0.66 0.84 0.74 21397219
accuracy 0.73 47511165
macro avg 0.75 0.74 0.73 47511165
weighted avg 0.76 0.73 0.73 47511165
Accuracy: 0.7331493976205382
precision recall f1-score support
0 0.07 0.05 0.06 41616
1 0.96 0.98 0.97 1064279
accuracy 0.94 1105895
macro avg 0.52 0.51 0.51 1105895
weighted avg 0.93 0.94 0.94 1105895
Accuracy: 0.9421988525131229
80-90%
precision recall f1-score support
0 0.06 0.06 0.06 3093
1 0.98 0.98 0.98 120943
accuracy 0.95 124036
macro avg 0.52 0.52 0.52 124036
weighted avg 0.95 0.95 0.95 124036
Accuracy: 0.9537311748202135
90-100%
precision recall f1-score support
0 0.06 0.06 0.06 2328
1 0.98 0.98 0.98 97067
accuracy 0.96 99395
macro avg 0.52 0.52 0.52 99395
weighted avg 0.96 0.96 0.96 99395
Accuracy: 0.9557724231601187
Treshold: 0.6
All
precision recall f1-score support
0 0.77 0.74 0.76 26119367
1 0.70 0.74 0.72 21615229
accuracy 0.74 47734596
macro avg 0.74 0.74 0.74 47734596
weighted avg 0.74 0.74 0.74 47734596
Accuracy: 0.7409371391767933
0-1%
precision recall f1-score support
0 0.96 0.95 0.96 12053010
1 0.11 0.15 0.13 508421
accuracy 0.92 12561431
macro avg 0.54 0.55 0.54 12561431
weighted avg 0.93 0.92 0.92 12561431
Accuracy: 0.9176135266754242
1-10%
precision recall f1-score support
0 0.62 0.59 0.61 13368467
1 0.64 0.67 0.65 14466820
accuracy 0.63 27835287
macro avg 0.63 0.63 0.63 27835287
weighted avg 0.63 0.63 0.63 27835287
Accuracy: 0.6313735511331354
10-20%
precision recall f1-score support
0 0.18 0.11 0.14 503365
1 0.88 0.92 0.90 3387274
accuracy 0.82 3890639
macro avg 0.53 0.52 0.52 3890639
weighted avg 0.79 0.82 0.80 3890639
Accuracy: 0.8199527121380318
20-40%
precision recall f1-score support
0 0.10 0.09 0.10 147488
1 0.93 0.94 0.94 1970425
accuracy 0.88 2117913
macro avg 0.52 0.52 0.52 2117913
weighted avg 0.87 0.88 0.88 2117913
Accuracy: 0.8805451404283368
40-80%
precision recall f1-score support
0 0.06 0.09 0.07 41616
1 0.96 0.94 0.95 1064279
accuracy 0.91 1105895
macro avg 0.51 0.52 0.51 1105895
weighted avg 0.93 0.91 0.92 1105895
Accuracy: 0.910039379868794
80-90%
precision recall f1-score support
0 0.04 0.10 0.06 3093
1 0.98 0.94 0.96 120943
accuracy 0.92 124036
macro avg 0.51 0.52 0.51 124036
weighted avg 0.95 0.92 0.94 124036
Accuracy: 0.9204343900158019
90-100%
precision recall f1-score support
0 0.04 0.10 0.06 2328
1 0.98 0.94 0.96 97067
accuracy 0.92 99395
macro avg 0.51 0.52 0.51 99395
weighted avg 0.96 0.92 0.94 99395
Accuracy: 0.922571557925449
Treshold: 0.7
All
precision recall f1-score support
0 0.69 0.86 0.77 26119367
1 0.76 0.54 0.63 21615229
accuracy 0.71 47734596
macro avg 0.73 0.70 0.70 47734596
weighted avg 0.72 0.71 0.71 47734596
Accuracy: 0.7148143455534849
0-1%
precision recall f1-score support
0 0.96 0.98 0.97 12053010
1 0.15 0.08 0.10 508421
accuracy 0.95 12561431
macro avg 0.56 0.53 0.54 12561431
weighted avg 0.93 0.95 0.94 12561431
Accuracy: 0.9455579543445328
1-10%
precision recall f1-score support
0 0.56 0.78 0.65 13368467
1 0.68 0.43 0.53 14466820
accuracy 0.60 27835287
macro avg 0.62 0.60 0.59 27835287
weighted avg 0.62 0.60 0.59 27835287
Accuracy: 0.5979673570457528
10-20%
precision recall f1-score support
0 0.17 0.28 0.21 503365
1 0.88 0.79 0.84 3387274
accuracy 0.73 3890639
macro avg 0.53 0.54 0.52 3890639
weighted avg 0.79 0.73 0.75 3890639
Accuracy: 0.7277953570094784
20-40%
precision recall f1-score support
0 0.10 0.24 0.14 147488
1 0.94 0.83 0.88 1970425
accuracy 0.79 2117913
macro avg 0.52 0.53 0.51 2117913
weighted avg 0.88 0.79 0.83 2117913
Accuracy: 0.7921571849268596
40-80%
precision recall f1-score support
0 0.05 0.23 0.09 41616
1 0.97 0.84 0.90 1064279
accuracy 0.82 1105895
macro avg 0.51 0.53 0.49 1105895
weighted avg 0.93 0.82 0.87 1105895
Accuracy: 0.8188960073062994
80-90%
precision recall f1-score support
0 0.04 0.24 0.06 3093
1 0.98 0.84 0.90 120943
accuracy 0.82 124036
macro avg 0.51 0.54 0.48 124036
weighted avg 0.95 0.82 0.88 124036
Accuracy: 0.8241800767519107
90-100%
precision recall f1-score support
0 0.03 0.23 0.06 2328
1 0.98 0.84 0.90 97067
accuracy 0.83 99395
macro avg 0.51 0.53 0.48 99395
weighted avg 0.96 0.83 0.88 99395
Accuracy: 0.8256954575179838
Treshold: 0.8
All
precision recall f1-score support
0 0.58 0.98 0.73 26119367
1 0.85 0.15 0.26 21615229
accuracy 0.60 47734596
macro avg 0.72 0.57 0.49 47734596
weighted avg 0.70 0.60 0.52 47734596
Accuracy: 0.6040380021232399
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.25 0.01 0.02 508421
accuracy 0.96 12561431
macro avg 0.61 0.50 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9588680620862384
1-10%
precision recall f1-score support
0 0.49 0.97 0.65 13368467
1 0.72 0.07 0.12 14466820
accuracy 0.50 27835287
macro avg 0.60 0.52 0.39 27835287
weighted avg 0.61 0.50 0.38 27835287
Accuracy: 0.5017235856055661
10-20%
precision recall f1-score support
0 0.14 0.77 0.23 503365
1 0.89 0.27 0.41 3387274
accuracy 0.33 3890639
macro avg 0.51 0.52 0.32 3890639
weighted avg 0.79 0.33 0.39 3890639
Accuracy: 0.33489614430945663
20-40%
precision recall f1-score support
0 0.07 0.63 0.13 147488
1 0.94 0.41 0.57 1970425
accuracy 0.43 2117913
macro avg 0.51 0.52 0.35 2117913
weighted avg 0.88 0.43 0.54 2117913
Accuracy: 0.42843166834520585
40-80%
precision recall f1-score support
0 0.04 0.59 0.08 41616
1 0.97 0.46 0.62 1064279
accuracy 0.46 1105895
macro avg 0.50 0.52 0.35 1105895
weighted avg 0.93 0.46 0.60 1105895
Accuracy: 0.4614669566278896
80-90%
precision recall f1-score support
0 0.03 0.60 0.05 3093
1 0.98 0.46 0.62 120943
accuracy 0.46 124036
macro avg 0.50 0.53 0.34 124036
weighted avg 0.95 0.46 0.61 124036
Accuracy: 0.46047921571156764
90-100%
precision recall f1-score support
0 0.02 0.57 0.05 2328
1 0.98 0.45 0.62 97067
accuracy 0.46 99395
macro avg 0.50 0.51 0.33 99395
weighted avg 0.96 0.46 0.61 99395
Accuracy: 0.45620001006086824
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.00 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.27 0.50 0.35 47734596
weighted avg 0.30 0.55 0.39 47734596
Accuracy: 0.5471720762023418
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.00 0.00 0.00 508421
accuracy 0.96 12561431
macro avg 0.48 0.50 0.49 12561431
weighted avg 0.92 0.96 0.94 12561431
Accuracy: 0.9594990411522382
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.00 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.24 0.50 0.32 27835287
weighted avg 0.23 0.48 0.31 27835287
Accuracy: 0.4802704926304514
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.00 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.06 0.50 0.11 3890639
weighted avg 0.02 0.13 0.03 3890639
Accuracy: 0.12937849026856513
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.00 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.03 0.50 0.07 2117913
weighted avg 0.00 0.07 0.01 2117913
Accuracy: 0.0696383656930195
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 0.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.02 0.50 0.04 1105895
weighted avg 0.00 0.04 0.00 1105895
Accuracy: 0.03763105900650604
80-90%
precision recall f1-score support
0 0.02 1.00 0.05 3093
1 0.00 0.00 0.00 120943
accuracy 0.02 124036
macro avg 0.01 0.50 0.02 124036
weighted avg 0.00 0.02 0.00 124036
Accuracy: 0.024936308813570254
90-100%
precision recall f1-score support
0 0.02 1.00 0.05 2328
1 0.00 0.00 0.00 97067
accuracy 0.02 99395
macro avg 0.01 0.50 0.02 99395
weighted avg 0.00 0.02 0.00 99395
Accuracy: 0.023421701292821572
0.2
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.48 0.63 24893266
1 0.60 0.95 0.74 20563095
accuracy 0.69 45456361
macro avg 0.76 0.72 0.68 45456361
weighted avg 0.77 0.69 0.68 45456361
Accuracy: 0.6929913945377194
0-1%
precision recall f1-score support
0 1.00 0.95 0.98 4873589
1 0.00 0.18 0.01 3872
accuracy 0.95 4877461
macro avg 0.50 0.56 0.49 4877461
weighted avg 1.00 0.95 0.97 4877461
Accuracy: 0.9517591222154314
1-10%
precision recall f1-score support
0 0.88 0.43 0.58 16949103
1 0.42 0.88 0.57 8016772
accuracy 0.58 24965875
macro avg 0.65 0.66 0.57 24965875
weighted avg 0.73 0.58 0.58 24965875
Accuracy: 0.5750368052391515
10-20%
precision recall f1-score support
0 0.45 0.03 0.05 2057494
1 0.73 0.99 0.84 5461156
accuracy 0.72 7518650
macro avg 0.59 0.51 0.44 7518650
weighted avg 0.65 0.72 0.62 7518650
Accuracy: 0.7249188351632274
20-40%
precision recall f1-score support
0 0.32 0.02 0.04 744974
1 0.85 0.99 0.91 4060539
accuracy 0.84 4805513
macro avg 0.58 0.51 0.48 4805513
weighted avg 0.76 0.84 0.78 4805513
Accuracy: 0.8414982958114982
40-80%
precision recall f1-score support
0 0.26 0.02 0.04 235909
1 0.91 0.99 0.95 2483775
accuracy 0.91 2719684
macro avg 0.58 0.51 0.50 2719684
weighted avg 0.86 0.91 0.87 2719684
Accuracy: 0.9094442589653798
80-90%
precision recall f1-score support
0 0.23 0.03 0.05 18577
1 0.94 0.99 0.97 296772
accuracy 0.94 315349
macro avg 0.59 0.51 0.51 315349
weighted avg 0.90 0.94 0.91 315349
Accuracy: 0.9372504748706988
90-100%
precision recall f1-score support
0 0.22 0.03 0.05 13620
1 0.95 0.99 0.97 240209
accuracy 0.94 253829
macro avg 0.58 0.51 0.51 253829
weighted avg 0.91 0.94 0.92 253829
Accuracy: 0.9423588321271407
Treshold: 0.5
All
precision recall f1-score support
0 0.83 0.65 0.73 24893266
1 0.66 0.85 0.74 20563095
accuracy 0.74 45456361
macro avg 0.75 0.75 0.74 45456361
weighted avg 0.76 0.74 0.74 45456361
Accuracy: 0.7366924730292422
precision recall f1-score support
0 0.83 0.65 0.73 24893266
1 0.66 0.85 0.74 20563095
accuracy 0.74 45456361
macro avg 0.75 0.75 0.74 45456361
weighted avg 0.76 0.74 0.74 45456361
Accuracy: 0.7366924730292422
0-1%
precision recall f1-score support
0 1.00 0.98 0.99 4873589
1 0.01 0.11 0.01 3872
accuracy 0.98 4877461
macro avg 0.50 0.55 0.50 4877461
weighted avg 1.00 0.98 0.99 4877461
Accuracy: 0.9834992017363132
precision recall f1-score support
0 1.00 0.98 0.99 4873589
1 0.01 0.11 0.01 3872
accuracy 0.98 4877461
macro avg 0.50 0.55 0.50 4877461
weighted avg 1.00 0.98 0.99 4877461
Accuracy: 0.9834992017363132
1-10%
precision recall f1-score support
0 0.81 0.65 0.72 16949103
1 0.48 0.69 0.56 8016772
accuracy 0.66 24965875
macro avg 0.65 0.67 0.64 24965875
weighted avg 0.71 0.66 0.67 24965875
Accuracy: 0.6596058820289695
precision recall f1-score support
0 0.86 0.72 0.79 21822692
1 0.48 0.69 0.56 8020644
accuracy 0.71 29843336
macro avg 0.67 0.70 0.67 29843336
weighted avg 0.76 0.71 0.73 29843336
Accuracy: 0.7125415536654481
10-20%
precision recall f1-score support
0 0.85 0.67 0.75 23880186
1 0.57 0.79 0.66 13481800
accuracy 0.71 37361986
macro avg 0.71 0.73 0.71 37361986
weighted avg 0.75 0.71 0.72 37361986
Accuracy: 0.7125601674386367
precision recall f1-score support
0 0.42 0.13 0.19 2057494
1 0.74 0.93 0.83 5461156
accuracy 0.71 7518650
macro avg 0.58 0.53 0.51 7518650
weighted avg 0.65 0.71 0.65 7518650
Accuracy: 0.7126340499956774
20-40%
precision recall f1-score support
0 0.84 0.65 0.73 24625160
1 0.63 0.82 0.71 17542339
accuracy 0.72 42167499
macro avg 0.73 0.74 0.72 42167499
weighted avg 0.75 0.72 0.73 42167499
Accuracy: 0.7247647293475954
precision recall f1-score support
0 0.25 0.08 0.13 744974
1 0.85 0.95 0.90 4060539
accuracy 0.82 4805513
macro avg 0.55 0.52 0.51 4805513
weighted avg 0.76 0.82 0.78 4805513
Accuracy: 0.8196529694124228
40-80%
precision recall f1-score support
0 0.16 0.08 0.10 235909
1 0.92 0.96 0.94 2483775
accuracy 0.88 2719684
macro avg 0.54 0.52 0.52 2719684
weighted avg 0.85 0.88 0.87 2719684
Accuracy: 0.8846141684107418
precision recall f1-score support
0 0.84 0.65 0.73 24861069
1 0.66 0.84 0.74 20026114
accuracy 0.73 44887183
macro avg 0.75 0.74 0.73 44887183
weighted avg 0.76 0.73 0.73 44887183
Accuracy: 0.7344498985378521
80-90%
precision recall f1-score support
0 0.12 0.08 0.09 18577
1 0.94 0.96 0.95 296772
accuracy 0.91 315349
macro avg 0.53 0.52 0.52 315349
weighted avg 0.89 0.91 0.90 315349
Accuracy: 0.9114885412669772
90-100%
precision recall f1-score support
0 0.10 0.07 0.09 13620
1 0.95 0.96 0.96 240209
accuracy 0.92 253829
macro avg 0.53 0.52 0.52 253829
weighted avg 0.90 0.92 0.91 253829
Accuracy: 0.9161088764483176
Treshold: 0.6
All
precision recall f1-score support
0 0.78 0.75 0.76 24893266
1 0.71 0.74 0.72 20563095
accuracy 0.74 45456361
macro avg 0.74 0.74 0.74 45456361
weighted avg 0.74 0.74 0.74 45456361
Accuracy: 0.7428688363329392
0-1%
precision recall f1-score support
0 1.00 0.99 1.00 4873589
1 0.01 0.07 0.02 3872
accuracy 0.99 4877461
macro avg 0.50 0.53 0.51 4877461
weighted avg 1.00 0.99 1.00 4877461
Accuracy: 0.9929309532152076
1-10%
precision recall f1-score support
0 0.77 0.77 0.77 16949103
1 0.51 0.52 0.52 8016772
accuracy 0.69 24965875
macro avg 0.64 0.64 0.64 24965875
weighted avg 0.69 0.69 0.69 24965875
Accuracy: 0.6879734838053944
10-20%
precision recall f1-score support
0 0.40 0.26 0.32 2057494
1 0.75 0.85 0.80 5461156
accuracy 0.69 7518650
macro avg 0.57 0.56 0.56 7518650
weighted avg 0.66 0.69 0.67 7518650
Accuracy: 0.6884822408278082
20-40%
precision recall f1-score support
0 0.24 0.18 0.20 744974
1 0.86 0.90 0.88 4060539
accuracy 0.79 4805513
macro avg 0.55 0.54 0.54 4805513
weighted avg 0.76 0.79 0.77 4805513
Accuracy: 0.7853706773865766
40-80%
precision recall f1-score support
0 0.14 0.15 0.15 235909
1 0.92 0.91 0.92 2483775
accuracy 0.85 2719684
macro avg 0.53 0.53 0.53 2719684
weighted avg 0.85 0.85 0.85 2719684
Accuracy: 0.846118151961772
80-90%
precision recall f1-score support
0 0.10 0.15 0.12 18577
1 0.94 0.92 0.93 296772
accuracy 0.87 315349
macro avg 0.52 0.53 0.52 315349
weighted avg 0.90 0.87 0.88 315349
Accuracy: 0.8717547859672934
90-100%
precision recall f1-score support
0 0.09 0.14 0.11 13620
1 0.95 0.92 0.93 240209
accuracy 0.88 253829
macro avg 0.52 0.53 0.52 253829
weighted avg 0.90 0.88 0.89 253829
Accuracy: 0.8770668442140181
Treshold: 0.7
All
precision recall f1-score support
0 0.70 0.86 0.77 24893266
1 0.76 0.54 0.64 20563095
accuracy 0.72 45456361
macro avg 0.73 0.70 0.70 45456361
weighted avg 0.73 0.72 0.71 45456361
Accuracy: 0.7167501155668841
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.02 0.03 0.03 3872
accuracy 1.00 4877461
macro avg 0.51 0.52 0.51 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9978810696794911
1-10%
precision recall f1-score support
0 0.73 0.89 0.80 16949103
1 0.56 0.29 0.38 8016772
accuracy 0.70 24965875
macro avg 0.64 0.59 0.59 24965875
weighted avg 0.67 0.70 0.67 24965875
Accuracy: 0.6979341601285755
10-20%
precision recall f1-score support
0 0.34 0.52 0.41 2057494
1 0.78 0.63 0.69 5461156
accuracy 0.60 7518650
macro avg 0.56 0.57 0.55 7518650
weighted avg 0.66 0.60 0.62 7518650
Accuracy: 0.5978731554201885
20-40%
precision recall f1-score support
0 0.22 0.38 0.28 744974
1 0.87 0.75 0.80 4060539
accuracy 0.69 4805513
macro avg 0.54 0.56 0.54 4805513
weighted avg 0.77 0.69 0.72 4805513
Accuracy: 0.6913786311679939
40-80%
precision recall f1-score support
0 0.13 0.33 0.19 235909
1 0.93 0.79 0.85 2483775
accuracy 0.75 2719684
macro avg 0.53 0.56 0.52 2719684
weighted avg 0.86 0.75 0.79 2719684
Accuracy: 0.7468573554868875
80-90%
precision recall f1-score support
0 0.09 0.31 0.14 18577
1 0.95 0.80 0.87 296772
accuracy 0.77 315349
macro avg 0.52 0.56 0.50 315349
weighted avg 0.90 0.77 0.82 315349
Accuracy: 0.7707206935807629
90-100%
precision recall f1-score support
0 0.08 0.31 0.13 13620
1 0.95 0.80 0.87 240209
accuracy 0.78 253829
macro avg 0.52 0.56 0.50 253829
weighted avg 0.91 0.78 0.83 253829
Accuracy: 0.7772910108774017
Treshold: 0.8
All
precision recall f1-score support
0 0.59 0.97 0.73 24893266
1 0.83 0.17 0.28 20563095
accuracy 0.61 45456361
macro avg 0.71 0.57 0.51 45456361
weighted avg 0.69 0.61 0.53 45456361
Accuracy: 0.6085714824378484
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.00 0.01 3872
accuracy 1.00 4877461
macro avg 0.53 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991608338846789
1-10%
precision recall f1-score support
0 0.69 0.98 0.81 16949103
1 0.62 0.06 0.11 8016772
accuracy 0.69 24965875
macro avg 0.65 0.52 0.46 24965875
weighted avg 0.67 0.69 0.59 24965875
Accuracy: 0.6863939677660006
10-20%
precision recall f1-score support
0 0.28 0.90 0.43 2057494
1 0.79 0.15 0.25 5461156
accuracy 0.35 7518650
macro avg 0.54 0.52 0.34 7518650
weighted avg 0.66 0.35 0.30 7518650
Accuracy: 0.3544235999813796
20-40%
precision recall f1-score support
0 0.17 0.81 0.28 744974
1 0.88 0.26 0.40 4060539
accuracy 0.35 4805513
macro avg 0.52 0.53 0.34 4805513
weighted avg 0.77 0.35 0.38 4805513
Accuracy: 0.34678961434502414
40-80%
precision recall f1-score support
0 0.10 0.72 0.17 235909
1 0.93 0.37 0.53 2483775
accuracy 0.40 2719684
macro avg 0.51 0.54 0.35 2719684
weighted avg 0.86 0.40 0.49 2719684
Accuracy: 0.39642436400699493
80-90%
precision recall f1-score support
0 0.07 0.68 0.12 18577
1 0.95 0.41 0.57 296772
accuracy 0.43 315349
macro avg 0.51 0.54 0.35 315349
weighted avg 0.90 0.43 0.55 315349
Accuracy: 0.4260454290325956
90-100%
precision recall f1-score support
0 0.06 0.67 0.11 13620
1 0.96 0.42 0.58 240209
accuracy 0.43 253829
macro avg 0.51 0.54 0.35 253829
weighted avg 0.91 0.43 0.56 253829
Accuracy: 0.4328110657174712
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.00 0.00 0.00 20563095
accuracy 0.55 45456361
macro avg 0.27 0.50 0.35 45456361
weighted avg 0.30 0.55 0.39 45456361
Accuracy: 0.5476299785633962
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.00 0.00 0.00 3872
accuracy 1.00 4877461
macro avg 0.50 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9992061443443627
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.00 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.34 0.50 0.40 24965875
weighted avg 0.46 0.68 0.55 24965875
Accuracy: 0.678890805950122
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.00 0.00 0.00 5461156
accuracy 0.27 7518650
macro avg 0.14 0.50 0.21 7518650
weighted avg 0.07 0.27 0.12 7518650
Accuracy: 0.2736520518976146
20-40%
precision recall f1-score support
0 0.16 1.00 0.27 744974
1 0.00 0.00 0.00 4060539
accuracy 0.16 4805513
macro avg 0.08 0.50 0.13 4805513
weighted avg 0.02 0.16 0.04 4805513
Accuracy: 0.15502486415082012
40-80%
precision recall f1-score support
0 0.09 1.00 0.16 235909
1 0.00 0.00 0.00 2483775
accuracy 0.09 2719684
macro avg 0.04 0.50 0.08 2719684
weighted avg 0.01 0.09 0.01 2719684
Accuracy: 0.08674132730126
80-90%
precision recall f1-score support
0 0.06 1.00 0.11 18577
1 0.00 0.00 0.00 296772
accuracy 0.06 315349
macro avg 0.03 0.50 0.06 315349
weighted avg 0.00 0.06 0.01 315349
Accuracy: 0.05890933537128705
90-100%
precision recall f1-score support
0 0.05 1.00 0.10 13620
1 0.00 0.00 0.00 240209
accuracy 0.05 253829
macro avg 0.03 0.50 0.05 253829
weighted avg 0.00 0.05 0.01 253829
Accuracy: 0.05365817144613105
0.4
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.50 0.64 22531902
1 0.58 0.95 0.72 16938696
accuracy 0.69 39470598
macro avg 0.75 0.72 0.68 39470598
weighted avg 0.78 0.69 0.68 39470598
Accuracy: 0.6886571366362374
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999606451359001
1-10%
precision recall f1-score support
0 0.95 0.74 0.83 11439888
1 0.22 0.67 0.33 1271288
accuracy 0.73 12711176
macro avg 0.59 0.70 0.58 12711176
weighted avg 0.88 0.73 0.78 12711176
Accuracy: 0.7289502560581335
10-20%
precision recall f1-score support
0 0.78 0.19 0.30 5044441
1 0.46 0.93 0.62 3812372
accuracy 0.51 8856813
macro avg 0.62 0.56 0.46 8856813
weighted avg 0.65 0.51 0.44 8856813
Accuracy: 0.5069575252407384
20-40%
precision recall f1-score support
0 0.59 0.06 0.12 2995598
1 0.66 0.98 0.79 5583215
accuracy 0.66 8578813
macro avg 0.62 0.52 0.45 8578813
weighted avg 0.63 0.66 0.55 8578813
Accuracy: 0.6575041325647266
40-80%
precision recall f1-score support
0 0.41 0.05 0.08 1295061
1 0.80 0.98 0.88 5001564
accuracy 0.79 6296625
macro avg 0.60 0.51 0.48 6296625
weighted avg 0.72 0.79 0.72 6296625
Accuracy: 0.7901089869572986
80-90%
precision recall f1-score support
0 0.33 0.05 0.08 117971
1 0.86 0.98 0.92 692761
accuracy 0.85 810732
macro avg 0.60 0.51 0.50 810732
weighted avg 0.78 0.85 0.80 810732
Accuracy: 0.8478597119640029
90-100%
precision recall f1-score support
0 0.32 0.05 0.08 88944
1 0.87 0.98 0.92 577496
accuracy 0.86 666440
macro avg 0.60 0.52 0.50 666440
weighted avg 0.80 0.86 0.81 666440
Accuracy: 0.8596662865374227
Treshold: 0.5
All
precision recall f1-score support
0 0.85 0.66 0.74 22531902
1 0.65 0.84 0.73 16938696
accuracy 0.74 39470598
macro avg 0.75 0.75 0.74 39470598
weighted avg 0.76 0.74 0.74 39470598
Accuracy: 0.7380751363331257
precision recall f1-score support
0 0.85 0.66 0.74 22531902
1 0.65 0.84 0.73 16938696
accuracy 0.74 39470598
macro avg 0.75 0.75 0.74 39470598
weighted avg 0.76 0.74 0.74 39470598
Accuracy: 0.7380751363331257
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999987096765869
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999987096765869
1-10%
precision recall f1-score support
0 0.94 0.89 0.91 12989887
1 0.27 0.42 0.33 1271288
accuracy 0.85 14261175
macro avg 0.61 0.65 0.62 14261175
weighted avg 0.88 0.85 0.86 14261175
Accuracy: 0.8480883938385161
precision recall f1-score support
0 0.93 0.88 0.90 11439888
1 0.27 0.42 0.33 1271288
accuracy 0.83 12711176
macro avg 0.60 0.65 0.62 12711176
weighted avg 0.87 0.83 0.85 12711176
Accuracy: 0.8295643927831697
10-20%
precision recall f1-score support
0 0.89 0.77 0.83 18034328
1 0.46 0.68 0.54 5083660
accuracy 0.75 23117988
macro avg 0.68 0.72 0.69 23117988
weighted avg 0.80 0.75 0.77 23117988
Accuracy: 0.7513015406011977
precision recall f1-score support
0 0.72 0.47 0.57 5044441
1 0.52 0.76 0.62 3812372
accuracy 0.60 8856813
macro avg 0.62 0.62 0.59 8856813
weighted avg 0.64 0.60 0.59 8856813
Accuracy: 0.5954560630330572
20-40%
precision recall f1-score support
0 0.55 0.23 0.33 2995598
1 0.69 0.90 0.78 5583215
accuracy 0.67 8578813
macro avg 0.62 0.57 0.55 8578813
weighted avg 0.64 0.67 0.62 8578813
Accuracy: 0.6660389963040342
40-80%
precision recall f1-score support
0 0.85 0.66 0.75 22324987
1 0.64 0.83 0.72 15668439
accuracy 0.73 37993426
macro avg 0.74 0.75 0.73 37993426
weighted avg 0.76 0.73 0.74 37993426
Accuracy: 0.7348150177349102
precision recall f1-score support
0 0.36 0.17 0.23 1295061
1 0.81 0.92 0.86 5001564
accuracy 0.77 6296625
macro avg 0.59 0.55 0.55 6296625
weighted avg 0.72 0.77 0.73 6296625
Accuracy: 0.7679885653028408
80-90%
precision recall f1-score support
0 0.28 0.16 0.20 117971
1 0.87 0.93 0.90 692761
accuracy 0.82 810732
macro avg 0.57 0.54 0.55 810732
weighted avg 0.78 0.82 0.80 810732
Accuracy: 0.8173909504003789
90-100%
precision recall f1-score support
0 0.26 0.15 0.19 88944
1 0.88 0.93 0.90 577496
accuracy 0.83 666440
macro avg 0.57 0.54 0.55 666440
weighted avg 0.79 0.83 0.81 666440
Accuracy: 0.8274458315827381
Treshold: 0.6
All
precision recall f1-score support
0 0.79 0.76 0.77 22531902
1 0.69 0.74 0.72 16938696
accuracy 0.75 39470598
macro avg 0.74 0.75 0.74 39470598
weighted avg 0.75 0.75 0.75 39470598
Accuracy: 0.7480763022642829
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999993548382935
1-10%
precision recall f1-score support
0 0.92 0.93 0.92 11439888
1 0.31 0.30 0.30 1271288
accuracy 0.86 12711176
macro avg 0.62 0.61 0.61 12711176
weighted avg 0.86 0.86 0.86 12711176
Accuracy: 0.863745494516007
10-20%
precision recall f1-score support
0 0.68 0.64 0.66 5044441
1 0.56 0.60 0.58 3812372
accuracy 0.63 8856813
macro avg 0.62 0.62 0.62 8856813
weighted avg 0.63 0.63 0.63 8856813
Accuracy: 0.6257444974845918
20-40%
precision recall f1-score support
0 0.52 0.40 0.45 2995598
1 0.71 0.80 0.76 5583215
accuracy 0.66 8578813
macro avg 0.62 0.60 0.60 8578813
weighted avg 0.65 0.66 0.65 8578813
Accuracy: 0.6613930155605443
40-80%
precision recall f1-score support
0 0.34 0.30 0.32 1295061
1 0.82 0.85 0.84 5001564
accuracy 0.74 6296625
macro avg 0.58 0.57 0.58 6296625
weighted avg 0.72 0.74 0.73 6296625
Accuracy: 0.7355327655688564
80-90%
precision recall f1-score support
0 0.25 0.28 0.27 117971
1 0.88 0.86 0.87 692761
accuracy 0.77 810732
macro avg 0.56 0.57 0.57 810732
weighted avg 0.78 0.77 0.78 810732
Accuracy: 0.7745383184578875
90-100%
precision recall f1-score support
0 0.24 0.27 0.25 88944
1 0.89 0.86 0.87 577496
accuracy 0.78 666440
macro avg 0.56 0.57 0.56 666440
weighted avg 0.80 0.78 0.79 666440
Accuracy: 0.7838875217573975
Treshold: 0.7
All
precision recall f1-score support
0 0.72 0.86 0.78 22531902
1 0.75 0.55 0.64 16938696
accuracy 0.73 39470598
macro avg 0.74 0.71 0.71 39470598
weighted avg 0.73 0.73 0.72 39470598
Accuracy: 0.7295519059528817
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.91 0.97 0.94 11439888
1 0.37 0.17 0.24 1271288
accuracy 0.89 12711176
macro avg 0.64 0.57 0.59 12711176
weighted avg 0.86 0.89 0.87 12711176
Accuracy: 0.8877083442161449
10-20%
precision recall f1-score support
0 0.64 0.82 0.71 5044441
1 0.61 0.38 0.47 3812372
accuracy 0.63 8856813
macro avg 0.62 0.60 0.59 8856813
weighted avg 0.62 0.63 0.61 8856813
Accuracy: 0.629026716494974
20-40%
precision recall f1-score support
0 0.46 0.64 0.54 2995598
1 0.76 0.60 0.67 5583215
accuracy 0.62 8578813
macro avg 0.61 0.62 0.60 8578813
weighted avg 0.65 0.62 0.62 8578813
Accuracy: 0.6154998366324106
40-80%
precision recall f1-score support
0 0.30 0.53 0.39 1295061
1 0.85 0.68 0.76 5001564
accuracy 0.65 6296625
macro avg 0.58 0.61 0.57 6296625
weighted avg 0.74 0.65 0.68 6296625
Accuracy: 0.6527463522124948
80-90%
precision recall f1-score support
0 0.22 0.50 0.31 117971
1 0.89 0.70 0.79 692761
accuracy 0.67 810732
macro avg 0.56 0.60 0.55 810732
weighted avg 0.79 0.67 0.72 810732
Accuracy: 0.6739588421327887
90-100%
precision recall f1-score support
0 0.21 0.49 0.29 88944
1 0.90 0.71 0.79 577496
accuracy 0.68 666440
macro avg 0.55 0.60 0.54 666440
weighted avg 0.81 0.68 0.73 666440
Accuracy: 0.6813891723185883
Treshold: 0.8
All
precision recall f1-score support
0 0.62 0.96 0.76 22531902
1 0.82 0.23 0.36 16938696
accuracy 0.65 39470598
macro avg 0.72 0.60 0.56 39470598
weighted avg 0.71 0.65 0.59 39470598
Accuracy: 0.648759767967032
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 0.99 0.95 11439888
1 0.47 0.06 0.10 1271288
accuracy 0.90 12711176
macro avg 0.69 0.52 0.52 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.899239928705259
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.13 0.22 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.48 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5995566351011362
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.81 0.23 0.36 5583215
accuracy 0.47 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.66 0.47 0.43 8578813
Accuracy: 0.46709667176566266
40-80%
precision recall f1-score support
0 0.24 0.84 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.43 6296625
macro avg 0.56 0.58 0.42 6296625
weighted avg 0.75 0.43 0.45 6296625
Accuracy: 0.4279365533122903
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.42 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.42 0.47 810732
Accuracy: 0.41600306883162375
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.36 0.51 577496
accuracy 0.42 666440
macro avg 0.54 0.58 0.39 666440
weighted avg 0.82 0.42 0.48 666440
Accuracy: 0.41627303283116257
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.00 0.00 0.00 16938696
accuracy 0.57 39470598
macro avg 0.29 0.50 0.36 39470598
weighted avg 0.33 0.57 0.41 39470598
Accuracy: 0.5708528155565314
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 1.00 0.95 11439888
1 0.00 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.45 0.50 0.47 12711176
weighted avg 0.81 0.90 0.85 12711176
Accuracy: 0.8999865944740282
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.00 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.28 0.50 0.36 8856813
weighted avg 0.32 0.57 0.41 8856813
Accuracy: 0.5695548726161431
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.00 0.00 0.00 5583215
accuracy 0.35 8578813
macro avg 0.17 0.50 0.26 8578813
weighted avg 0.12 0.35 0.18 8578813
Accuracy: 0.34918560411562766
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.00 0.00 0.00 5001564
accuracy 0.21 6296625
macro avg 0.10 0.50 0.17 6296625
weighted avg 0.04 0.21 0.07 6296625
Accuracy: 0.20567542135667918
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.00 0.00 0.00 692761
accuracy 0.15 810732
macro avg 0.07 0.50 0.13 810732
weighted avg 0.02 0.15 0.04 810732
Accuracy: 0.14551171040491803
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.00 0.00 0.00 577496
accuracy 0.13 666440
macro avg 0.07 0.50 0.12 666440
weighted avg 0.02 0.13 0.03 666440
Accuracy: 0.13346137686813517
LR_9
0.01
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.46 0.62 28055468
1 0.58 0.95 0.72 21729815
accuracy 0.67 49785283
macro avg 0.75 0.71 0.67 49785283
weighted avg 0.77 0.67 0.66 49785283
Accuracy: 0.6748175560235341
0-1%
precision recall f1-score support
0 0.92 0.47 0.62 27764588
1 0.52 0.93 0.67 17098553
accuracy 0.65 44863141
macro avg 0.72 0.70 0.64 44863141
weighted avg 0.77 0.65 0.64 44863141
Accuracy: 0.6456711535199909
1-10%
precision recall f1-score support
0 0.19 0.00 0.00 287564
1 0.94 1.00 0.97 4164787
accuracy 0.93 4452351
macro avg 0.56 0.50 0.49 4452351
weighted avg 0.89 0.93 0.90 4452351
Accuracy: 0.9349646961796139
10-20%
precision recall f1-score support
0 0.28 0.01 0.02 2455
1 0.99 1.00 1.00 257616
accuracy 0.99 260071
macro avg 0.64 0.50 0.51 260071
weighted avg 0.98 0.99 0.99 260071
Accuracy: 0.9904141561342864
20-40%
precision recall f1-score support
0 0.19 0.02 0.04 659
1 1.00 1.00 1.00 130568
accuracy 0.99 131227
macro avg 0.59 0.51 0.52 131227
weighted avg 0.99 0.99 0.99 131227
Accuracy: 0.9946504911336844
40-80%
precision recall f1-score support
0 0.24 0.08 0.12 169
1 1.00 1.00 1.00 65234
accuracy 1.00 65403
macro avg 0.62 0.54 0.56 65403
weighted avg 1.00 1.00 1.00 65403
Accuracy: 0.9969726159350488
80-90%
precision recall f1-score support
0 0.12 0.07 0.09 15
1 1.00 1.00 1.00 7371
accuracy 1.00 7386
macro avg 0.56 0.53 0.54 7386
weighted avg 1.00 1.00 1.00 7386
Accuracy: 0.9971567831031681
90-100%
precision recall f1-score support
0 0.36 0.22 0.28 18
1 1.00 1.00 1.00 5686
accuracy 1.00 5704
macro avg 0.68 0.61 0.64 5704
weighted avg 1.00 1.00 1.00 5704
Accuracy: 0.9963183730715287
Treshold: 0.5
All
precision recall f1-score support
0 0.84 0.64 0.72 28055468
1 0.64 0.84 0.73 21729815
accuracy 0.72 49785283
macro avg 0.74 0.74 0.72 49785283
weighted avg 0.75 0.72 0.72 49785283
Accuracy: 0.7248628274343645
precision recall f1-score support
0 0.84 0.64 0.72 28055468
1 0.64 0.84 0.73 21729815
accuracy 0.72 49785283
macro avg 0.74 0.74 0.72 49785283
weighted avg 0.75 0.72 0.72 49785283
Accuracy: 0.72486278726185
0-1%
precision recall f1-score support
0 0.84 0.64 0.73 27764588
1 0.58 0.80 0.67 17098553
accuracy 0.70 44863141
macro avg 0.71 0.72 0.70 44863141
weighted avg 0.74 0.70 0.71 44863141
Accuracy: 0.701951341302652
1-10%
precision recall f1-score support
0 0.10 0.01 0.02 287564
1 0.94 0.99 0.96 4164787
accuracy 0.93 4452351
macro avg 0.52 0.50 0.49 4452351
weighted avg 0.88 0.93 0.90 4452351
Accuracy: 0.9280243179389944
precision recall f1-score support
0 0.84 0.64 0.72 28052152
1 0.64 0.84 0.72 21263340
accuracy 0.72 49315492
macro avg 0.74 0.74 0.72 49315492
weighted avg 0.75 0.72 0.72 49315492
Accuracy: 0.7223619506827591
10-20%
precision recall f1-score support
0 0.84 0.64 0.72 28054607
1 0.64 0.84 0.72 21520956
accuracy 0.72 49575563
macro avg 0.74 0.74 0.72 49575563
weighted avg 0.75 0.72 0.72 49575563
Accuracy: 0.7237477867876155
precision recall f1-score support
0 0.05 0.02 0.03 2455
1 0.99 1.00 0.99 257616
accuracy 0.99 260071
macro avg 0.52 0.51 0.51 260071
weighted avg 0.98 0.99 0.98 260071
Accuracy: 0.986534446362724
20-40%
precision recall f1-score support
0 0.84 0.64 0.72 28055266
1 0.64 0.84 0.73 21651524
accuracy 0.72 49706790
macro avg 0.74 0.74 0.72 49706790
weighted avg 0.75 0.72 0.72 49706790
Accuracy: 0.7244478269467813
precision recall f1-score support
0 0.03 0.04 0.03 659
1 1.00 0.99 0.99 130568
accuracy 0.99 131227
macro avg 0.51 0.52 0.51 131227
weighted avg 0.99 0.99 0.99 131227
Accuracy: 0.9889123427343458
40-80%
precision recall f1-score support
0 0.84 0.64 0.72 28055435
1 0.64 0.84 0.73 21716758
accuracy 0.72 49772193
macro avg 0.74 0.74 0.72 49772193
weighted avg 0.75 0.72 0.72 49772193
Accuracy: 0.7247940230401341
precision recall f1-score support
0 0.02 0.08 0.03 169
1 1.00 0.99 0.99 65234
accuracy 0.99 65403
macro avg 0.51 0.54 0.51 65403
weighted avg 1.00 0.99 0.99 65403
Accuracy: 0.9879057535587052
80-90%
precision recall f1-score support
0 0.01 0.07 0.02 15
1 1.00 0.99 0.99 7371
accuracy 0.99 7386
macro avg 0.51 0.53 0.51 7386
weighted avg 1.00 0.99 0.99 7386
Accuracy: 0.9879501760086651
90-100%
precision recall f1-score support
0 0.05 0.22 0.08 18
1 1.00 0.99 0.99 5686
accuracy 0.98 5704
macro avg 0.52 0.60 0.54 5704
weighted avg 0.99 0.98 0.99 5704
Accuracy: 0.9847475455820477
Treshold: 0.6
All
precision recall f1-score support
0 0.78 0.75 0.76 28055468
1 0.69 0.72 0.70 21729815
accuracy 0.74 49785283
macro avg 0.73 0.73 0.73 49785283
weighted avg 0.74 0.74 0.74 49785283
Accuracy: 0.7358201016955151
0-1%
precision recall f1-score support
0 0.78 0.75 0.77 27764588
1 0.62 0.66 0.64 17098553
accuracy 0.72 44863141
macro avg 0.70 0.70 0.70 44863141
weighted avg 0.72 0.72 0.72 44863141
Accuracy: 0.7158991609615564
1-10%
precision recall f1-score support
0 0.09 0.04 0.06 287564
1 0.94 0.97 0.95 4164787
accuracy 0.91 4452351
macro avg 0.51 0.51 0.51 4452351
weighted avg 0.88 0.91 0.90 4452351
Accuracy: 0.911357842182703
10-20%
precision recall f1-score support
0 0.02 0.04 0.03 2455
1 0.99 0.99 0.99 257616
accuracy 0.98 260071
macro avg 0.51 0.51 0.51 260071
weighted avg 0.98 0.98 0.98 260071
Accuracy: 0.9765602470094705
20-40%
precision recall f1-score support
0 0.02 0.06 0.02 659
1 1.00 0.98 0.99 130568
accuracy 0.98 131227
macro avg 0.51 0.52 0.51 131227
weighted avg 0.99 0.98 0.98 131227
Accuracy: 0.9756528763135636
40-80%
precision recall f1-score support
0 0.01 0.11 0.02 169
1 1.00 0.97 0.98 65234
accuracy 0.97 65403
macro avg 0.50 0.54 0.50 65403
weighted avg 1.00 0.97 0.98 65403
Accuracy: 0.9674938458480498
80-90%
precision recall f1-score support
0 0.01 0.13 0.01 15
1 1.00 0.96 0.98 7371
accuracy 0.96 7386
macro avg 0.50 0.55 0.50 7386
weighted avg 1.00 0.96 0.98 7386
Accuracy: 0.9615488762523694
90-100%
precision recall f1-score support
0 0.02 0.22 0.03 18
1 1.00 0.96 0.98 5686
accuracy 0.96 5704
macro avg 0.51 0.59 0.50 5704
weighted avg 0.99 0.96 0.97 5704
Accuracy: 0.9565217391304348
Treshold: 0.7
All
precision recall f1-score support
0 0.69 0.88 0.77 28055468
1 0.76 0.50 0.60 21729815
accuracy 0.71 49785283
macro avg 0.73 0.69 0.69 49785283
weighted avg 0.72 0.71 0.70 49785283
Accuracy: 0.712129606655043
0-1%
precision recall f1-score support
0 0.70 0.89 0.78 27764588
1 0.68 0.39 0.49 17098553
accuracy 0.70 44863141
macro avg 0.69 0.64 0.64 44863141
weighted avg 0.69 0.70 0.67 44863141
Accuracy: 0.6966158477401304
1-10%
precision recall f1-score support
0 0.08 0.14 0.10 287564
1 0.94 0.89 0.92 4164787
accuracy 0.85 4452351
macro avg 0.51 0.52 0.51 4452351
weighted avg 0.88 0.85 0.86 4452351
Accuracy: 0.8456411006230191
10-20%
precision recall f1-score support
0 0.01 0.07 0.02 2455
1 0.99 0.95 0.97 257616
accuracy 0.94 260071
macro avg 0.50 0.51 0.50 260071
weighted avg 0.98 0.94 0.96 260071
Accuracy: 0.9417466768690088
20-40%
precision recall f1-score support
0 0.01 0.12 0.02 659
1 1.00 0.93 0.96 130568
accuracy 0.93 131227
macro avg 0.50 0.52 0.49 131227
weighted avg 0.99 0.93 0.96 131227
Accuracy: 0.9254421727236011
40-80%
precision recall f1-score support
0 0.00 0.18 0.01 169
1 1.00 0.89 0.94 65234
accuracy 0.89 65403
macro avg 0.50 0.54 0.48 65403
weighted avg 1.00 0.89 0.94 65403
Accuracy: 0.8922067795055273
80-90%
precision recall f1-score support
0 0.00 0.13 0.00 15
1 1.00 0.87 0.93 7371
accuracy 0.87 7386
macro avg 0.50 0.50 0.47 7386
weighted avg 1.00 0.87 0.93 7386
Accuracy: 0.8701597617113458
90-100%
precision recall f1-score support
0 0.01 0.33 0.02 18
1 1.00 0.87 0.93 5686
accuracy 0.87 5704
macro avg 0.50 0.60 0.47 5704
weighted avg 0.99 0.87 0.93 5704
Accuracy: 0.8702664796633941
Treshold: 0.8
All
precision recall f1-score support
0 0.60 0.99 0.75 28055468
1 0.91 0.14 0.25 21729815
accuracy 0.62 49785283
macro avg 0.76 0.57 0.50 49785283
weighted avg 0.74 0.62 0.53 49785283
Accuracy: 0.6201705833428727
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.80 0.04 0.08 17098553
accuracy 0.63 44863141
macro avg 0.71 0.52 0.42 44863141
weighted avg 0.69 0.63 0.50 44863141
Accuracy: 0.6301739327614176
1-10%
precision recall f1-score support
0 0.07 0.58 0.13 287564
1 0.95 0.51 0.66 4164787
accuracy 0.51 4452351
macro avg 0.51 0.54 0.40 4452351
weighted avg 0.89 0.51 0.63 4452351
Accuracy: 0.5123178743095501
10-20%
precision recall f1-score support
0 0.01 0.25 0.02 2455
1 0.99 0.76 0.86 257616
accuracy 0.76 260071
macro avg 0.50 0.50 0.44 260071
weighted avg 0.98 0.76 0.85 260071
Accuracy: 0.7580083900165724
20-40%
precision recall f1-score support
0 0.01 0.36 0.01 659
1 1.00 0.67 0.80 130568
accuracy 0.66 131227
macro avg 0.50 0.51 0.40 131227
weighted avg 0.99 0.66 0.79 131227
Accuracy: 0.6647412498952198
40-80%
precision recall f1-score support
0 0.00 0.51 0.01 169
1 1.00 0.51 0.67 65234
accuracy 0.51 65403
macro avg 0.50 0.51 0.34 65403
weighted avg 0.99 0.51 0.67 65403
Accuracy: 0.5070409614237879
80-90%
precision recall f1-score support
0 0.00 0.60 0.00 15
1 1.00 0.40 0.57 7371
accuracy 0.40 7386
macro avg 0.50 0.50 0.29 7386
weighted avg 1.00 0.40 0.57 7386
Accuracy: 0.4018413214189006
90-100%
precision recall f1-score support
0 0.00 0.67 0.01 18
1 1.00 0.40 0.57 5686
accuracy 0.40 5704
macro avg 0.50 0.53 0.29 5704
weighted avg 0.99 0.40 0.57 5704
Accuracy: 0.39779102384291726
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 28055468
1 0.95 0.03 0.06 21729815
accuracy 0.58 49785283
macro avg 0.76 0.51 0.39 49785283
weighted avg 0.74 0.58 0.44 49785283
Accuracy: 0.5761586410988163
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.55 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.59 0.50 0.38 44863141
weighted avg 0.59 0.62 0.47 44863141
Accuracy: 0.6189119928094201
1-10%
precision recall f1-score support
0 0.07 0.92 0.13 287564
1 0.96 0.13 0.24 4164787
accuracy 0.19 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.19 0.23 4452351
Accuracy: 0.18560351598515032
10-20%
precision recall f1-score support
0 0.01 0.69 0.02 2455
1 0.99 0.30 0.47 257616
accuracy 0.31 260071
macro avg 0.50 0.50 0.24 260071
weighted avg 0.98 0.31 0.46 260071
Accuracy: 0.30831196096450586
20-40%
precision recall f1-score support
0 0.00 0.90 0.01 659
1 0.99 0.08 0.15 130568
accuracy 0.08 131227
macro avg 0.50 0.49 0.08 131227
weighted avg 0.99 0.08 0.15 131227
Accuracy: 0.08415950985696541
40-80%
precision recall f1-score support
0 0.00 1.00 0.01 169
1 1.00 0.00 0.00 65234
accuracy 0.00 65403
macro avg 0.50 0.50 0.00 65403
weighted avg 1.00 0.00 0.00 65403
Accuracy: 0.0038683240829931347
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 0.00 0.00 0.00 7371
accuracy 0.00 7386
macro avg 0.00 0.50 0.00 7386
weighted avg 0.00 0.00 0.00 7386
Accuracy: 0.0020308692120227455
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 0.00 0.00 0.00 5686
accuracy 0.00 5704
macro avg 0.00 0.50 0.00 5704
weighted avg 0.00 0.00 0.00 5704
Accuracy: 0.003155680224403927
0.1
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.48 0.63 26119367
1 0.60 0.95 0.73 21615229
accuracy 0.69 47734596
macro avg 0.76 0.71 0.68 47734596
weighted avg 0.77 0.69 0.68 47734596
Accuracy: 0.6898931123246544
0-1%
precision recall f1-score support
0 0.97 0.81 0.89 12053010
1 0.08 0.40 0.14 508421
accuracy 0.80 12561431
macro avg 0.53 0.61 0.51 12561431
weighted avg 0.93 0.80 0.86 12561431
Accuracy: 0.7980078065946468
1-10%
precision recall f1-score support
0 0.76 0.20 0.31 13368467
1 0.56 0.94 0.70 14466820
accuracy 0.58 27835287
macro avg 0.66 0.57 0.51 27835287
weighted avg 0.66 0.58 0.52 27835287
Accuracy: 0.5849552404471347
10-20%
precision recall f1-score support
0 0.27 0.01 0.02 503365
1 0.87 1.00 0.93 3387274
accuracy 0.87 3890639
macro avg 0.57 0.50 0.47 3890639
weighted avg 0.79 0.87 0.81 3890639
Accuracy: 0.868560151687165
20-40%
precision recall f1-score support
0 0.23 0.01 0.02 147488
1 0.93 1.00 0.96 1970425
accuracy 0.93 2117913
macro avg 0.58 0.50 0.49 2117913
weighted avg 0.88 0.93 0.90 2117913
Accuracy: 0.9284191560276556
40-80%
precision recall f1-score support
0 0.21 0.02 0.03 41616
1 0.96 1.00 0.98 1064279
accuracy 0.96 1105895
macro avg 0.58 0.51 0.51 1105895
weighted avg 0.93 0.96 0.94 1105895
Accuracy: 0.9603850275116534
80-90%
precision recall f1-score support
0 0.22 0.03 0.05 3093
1 0.98 1.00 0.99 120943
accuracy 0.97 124036
macro avg 0.60 0.51 0.52 124036
weighted avg 0.96 0.97 0.96 124036
Accuracy: 0.9732335773485117
90-100%
precision recall f1-score support
0 0.21 0.03 0.05 2328
1 0.98 1.00 0.99 97067
accuracy 0.97 99395
macro avg 0.59 0.51 0.52 99395
weighted avg 0.96 0.97 0.97 99395
Accuracy: 0.974757281553398
Treshold: 0.5
All
precision recall f1-score support
0 0.83 0.64 0.73 26119367
1 0.66 0.85 0.74 21615229
accuracy 0.73 47734596
macro avg 0.75 0.74 0.73 47734596
weighted avg 0.76 0.73 0.73 47734596
Accuracy: 0.7341014680421721
precision recall f1-score support
0 0.83 0.64 0.73 26119367
1 0.66 0.85 0.74 21615229
accuracy 0.73 47734596
macro avg 0.75 0.74 0.73 47734596
weighted avg 0.76 0.73 0.73 47734596
Accuracy: 0.7341014680421721
0-1%
precision recall f1-score support
0 0.97 0.91 0.94 12053010
1 0.10 0.23 0.14 508421
accuracy 0.88 12561431
macro avg 0.53 0.57 0.54 12561431
weighted avg 0.93 0.88 0.90 12561431
Accuracy: 0.8822924712956669
precision recall f1-score support
0 0.97 0.91 0.94 12053010
1 0.10 0.23 0.14 508421
accuracy 0.88 12561431
macro avg 0.53 0.57 0.54 12561431
weighted avg 0.93 0.88 0.90 12561431
Accuracy: 0.8822924712956669
1-10%
precision recall f1-score support
0 0.84 0.66 0.74 25421477
1 0.58 0.79 0.67 14975241
accuracy 0.71 40396718
macro avg 0.71 0.72 0.70 40396718
weighted avg 0.74 0.71 0.71 40396718
Accuracy: 0.7065304909176038
precision recall f1-score support
0 0.68 0.43 0.53 13368467
1 0.61 0.81 0.69 14466820
accuracy 0.63 27835287
macro avg 0.64 0.62 0.61 27835287
weighted avg 0.64 0.63 0.61 27835287
Accuracy: 0.6272131126221189
10-20%
precision recall f1-score support
0 0.84 0.65 0.73 25924842
1 0.62 0.82 0.71 18362515
accuracy 0.72 44287357
macro avg 0.73 0.73 0.72 44287357
weighted avg 0.75 0.72 0.72 44287357
Accuracy: 0.7192857772027353
precision recall f1-score support
0 0.20 0.05 0.08 503365
1 0.87 0.97 0.92 3387274
accuracy 0.85 3890639
macro avg 0.54 0.51 0.50 3890639
weighted avg 0.79 0.85 0.81 3890639
Accuracy: 0.8517246138744818
20-40%
precision recall f1-score support
0 0.84 0.64 0.73 26072330
1 0.65 0.84 0.73 20332940
accuracy 0.73 46405270
macro avg 0.74 0.74 0.73 46405270
weighted avg 0.75 0.73 0.73 46405270
Accuracy: 0.7280703032220263
precision recall f1-score support
0 0.12 0.04 0.06 147488
1 0.93 0.98 0.95 1970425
accuracy 0.91 2117913
macro avg 0.53 0.51 0.51 2117913
weighted avg 0.88 0.91 0.89 2117913
Accuracy: 0.9117621923091269
40-80%
precision recall f1-score support
0 0.83 0.64 0.73 26113946
1 0.66 0.84 0.74 21397219
accuracy 0.73 47511165
macro avg 0.75 0.74 0.73 47511165
weighted avg 0.76 0.73 0.73 47511165
Accuracy: 0.7330627863997863
precision recall f1-score support
0 0.07 0.05 0.06 41616
1 0.96 0.98 0.97 1064279
accuracy 0.94 1105895
macro avg 0.52 0.51 0.51 1105895
weighted avg 0.93 0.94 0.94 1105895
Accuracy: 0.9425560292794524
80-90%
precision recall f1-score support
0 0.06 0.06 0.06 3093
1 0.98 0.98 0.98 120943
accuracy 0.95 124036
macro avg 0.52 0.52 0.52 124036
weighted avg 0.95 0.95 0.95 124036
Accuracy: 0.954053661840111
90-100%
precision recall f1-score support
0 0.06 0.06 0.06 2328
1 0.98 0.98 0.98 97067
accuracy 0.96 99395
macro avg 0.52 0.52 0.52 99395
weighted avg 0.96 0.96 0.96 99395
Accuracy: 0.9561144926807184
Treshold: 0.6
All
precision recall f1-score support
0 0.77 0.74 0.76 26119367
1 0.70 0.74 0.72 21615229
accuracy 0.74 47734596
macro avg 0.74 0.74 0.74 47734596
weighted avg 0.74 0.74 0.74 47734596
Accuracy: 0.7409823684272933
0-1%
precision recall f1-score support
0 0.96 0.95 0.96 12053010
1 0.11 0.15 0.13 508421
accuracy 0.92 12561431
macro avg 0.54 0.55 0.54 12561431
weighted avg 0.93 0.92 0.92 12561431
Accuracy: 0.917398742229289
1-10%
precision recall f1-score support
0 0.62 0.59 0.61 13368467
1 0.64 0.67 0.65 14466820
accuracy 0.63 27835287
macro avg 0.63 0.63 0.63 27835287
weighted avg 0.63 0.63 0.63 27835287
Accuracy: 0.6313308714941578
10-20%
precision recall f1-score support
0 0.19 0.11 0.14 503365
1 0.88 0.93 0.90 3387274
accuracy 0.82 3890639
macro avg 0.53 0.52 0.52 3890639
weighted avg 0.79 0.82 0.80 3890639
Accuracy: 0.8207253358638517
20-40%
precision recall f1-score support
0 0.10 0.09 0.10 147488
1 0.93 0.94 0.94 1970425
accuracy 0.88 2117913
macro avg 0.52 0.52 0.52 2117913
weighted avg 0.87 0.88 0.88 2117913
Accuracy: 0.8813931450442015
40-80%
precision recall f1-score support
0 0.06 0.09 0.07 41616
1 0.96 0.94 0.95 1064279
accuracy 0.91 1105895
macro avg 0.51 0.52 0.51 1105895
weighted avg 0.93 0.91 0.92 1105895
Accuracy: 0.9109671352162728
80-90%
precision recall f1-score support
0 0.04 0.10 0.06 3093
1 0.98 0.94 0.96 120943
accuracy 0.92 124036
macro avg 0.51 0.52 0.51 124036
weighted avg 0.95 0.92 0.94 124036
Accuracy: 0.921490535005966
90-100%
precision recall f1-score support
0 0.04 0.10 0.06 2328
1 0.98 0.94 0.96 97067
accuracy 0.92 99395
macro avg 0.51 0.52 0.51 99395
weighted avg 0.96 0.92 0.94 99395
Accuracy: 0.923436792595201
Treshold: 0.7
All
precision recall f1-score support
0 0.69 0.86 0.77 26119367
1 0.76 0.54 0.63 21615229
accuracy 0.71 47734596
macro avg 0.73 0.70 0.70 47734596
weighted avg 0.72 0.71 0.71 47734596
Accuracy: 0.7148481784574022
0-1%
precision recall f1-score support
0 0.96 0.98 0.97 12053010
1 0.15 0.07 0.10 508421
accuracy 0.95 12561431
macro avg 0.56 0.53 0.54 12561431
weighted avg 0.93 0.95 0.94 12561431
Accuracy: 0.9455229264882321
1-10%
precision recall f1-score support
0 0.56 0.78 0.65 13368467
1 0.68 0.43 0.52 14466820
accuracy 0.60 27835287
macro avg 0.62 0.60 0.59 27835287
weighted avg 0.62 0.60 0.59 27835287
Accuracy: 0.5977541384789745
10-20%
precision recall f1-score support
0 0.17 0.28 0.21 503365
1 0.88 0.80 0.84 3387274
accuracy 0.73 3890639
macro avg 0.53 0.54 0.52 3890639
weighted avg 0.79 0.73 0.76 3890639
Accuracy: 0.72868389999689
20-40%
precision recall f1-score support
0 0.10 0.23 0.14 147488
1 0.94 0.84 0.88 1970425
accuracy 0.79 2117913
macro avg 0.52 0.53 0.51 2117913
weighted avg 0.88 0.79 0.83 2117913
Accuracy: 0.7933744209511912
40-80%
precision recall f1-score support
0 0.05 0.22 0.09 41616
1 0.97 0.84 0.90 1064279
accuracy 0.82 1105895
macro avg 0.51 0.53 0.49 1105895
weighted avg 0.93 0.82 0.87 1105895
Accuracy: 0.8203654053956297
80-90%
precision recall f1-score support
0 0.04 0.24 0.06 3093
1 0.98 0.84 0.90 120943
accuracy 0.83 124036
macro avg 0.51 0.54 0.48 124036
weighted avg 0.95 0.83 0.88 124036
Accuracy: 0.8257683253249056
90-100%
precision recall f1-score support
0 0.03 0.22 0.06 2328
1 0.98 0.84 0.90 97067
accuracy 0.83 99395
macro avg 0.51 0.53 0.48 99395
weighted avg 0.96 0.83 0.88 99395
Accuracy: 0.8270335529956235
Treshold: 0.8
All
precision recall f1-score support
0 0.58 0.98 0.73 26119367
1 0.85 0.15 0.26 21615229
accuracy 0.60 47734596
macro avg 0.72 0.56 0.49 47734596
weighted avg 0.70 0.60 0.51 47734596
Accuracy: 0.6032625687247882
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.25 0.01 0.02 508421
accuracy 0.96 12561431
macro avg 0.60 0.50 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9588855760143888
1-10%
precision recall f1-score support
0 0.49 0.97 0.65 13368467
1 0.72 0.07 0.12 14466820
accuracy 0.50 27835287
macro avg 0.60 0.52 0.39 27835287
weighted avg 0.61 0.50 0.38 27835287
Accuracy: 0.5011759713488854
10-20%
precision recall f1-score support
0 0.14 0.77 0.23 503365
1 0.89 0.27 0.41 3387274
accuracy 0.33 3890639
macro avg 0.51 0.52 0.32 3890639
weighted avg 0.79 0.33 0.39 3890639
Accuracy: 0.33145146594171293
20-40%
precision recall f1-score support
0 0.07 0.63 0.13 147488
1 0.94 0.41 0.57 1970425
accuracy 0.43 2117913
macro avg 0.51 0.52 0.35 2117913
weighted avg 0.88 0.43 0.54 2117913
Accuracy: 0.4257115377260539
40-80%
precision recall f1-score support
0 0.04 0.59 0.08 41616
1 0.97 0.45 0.62 1064279
accuracy 0.46 1105895
macro avg 0.50 0.52 0.35 1105895
weighted avg 0.93 0.46 0.60 1105895
Accuracy: 0.4593474063993417
80-90%
precision recall f1-score support
0 0.03 0.60 0.05 3093
1 0.98 0.45 0.62 120943
accuracy 0.46 124036
macro avg 0.50 0.53 0.34 124036
weighted avg 0.95 0.46 0.61 124036
Accuracy: 0.4583024283272598
90-100%
precision recall f1-score support
0 0.02 0.57 0.05 2328
1 0.98 0.45 0.62 97067
accuracy 0.45 99395
macro avg 0.50 0.51 0.33 99395
weighted avg 0.96 0.45 0.60 99395
Accuracy: 0.45403692338648827
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.00 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.27 0.50 0.35 47734596
weighted avg 0.30 0.55 0.39 47734596
Accuracy: 0.5471723275923399
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.00 0.00 0.00 508421
accuracy 0.96 12561431
macro avg 0.48 0.50 0.49 12561431
weighted avg 0.92 0.96 0.94 12561431
Accuracy: 0.95949999645741
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.00 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.24 0.50 0.32 27835287
weighted avg 0.23 0.48 0.31 27835287
Accuracy: 0.4802704926304514
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.00 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.06 0.50 0.11 3890639
weighted avg 0.02 0.13 0.03 3890639
Accuracy: 0.12937849026856513
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.00 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.03 0.50 0.07 2117913
weighted avg 0.00 0.07 0.01 2117913
Accuracy: 0.0696383656930195
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 0.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.02 0.50 0.04 1105895
weighted avg 0.00 0.04 0.00 1105895
Accuracy: 0.03763105900650604
80-90%
precision recall f1-score support
0 0.02 1.00 0.05 3093
1 0.00 0.00 0.00 120943
accuracy 0.02 124036
macro avg 0.01 0.50 0.02 124036
weighted avg 0.00 0.02 0.00 124036
Accuracy: 0.024936308813570254
90-100%
precision recall f1-score support
0 0.02 1.00 0.05 2328
1 0.00 0.00 0.00 97067
accuracy 0.02 99395
macro avg 0.01 0.50 0.02 99395
weighted avg 0.00 0.02 0.00 99395
Accuracy: 0.023421701292821572
0.2
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.48 0.63 24893266
1 0.60 0.95 0.74 20563095
accuracy 0.69 45456361
macro avg 0.76 0.71 0.68 45456361
weighted avg 0.77 0.69 0.68 45456361
Accuracy: 0.6928225072834141
0-1%
precision recall f1-score support
0 1.00 0.95 0.98 4873589
1 0.00 0.18 0.01 3872
accuracy 0.95 4877461
macro avg 0.50 0.56 0.49 4877461
weighted avg 1.00 0.95 0.97 4877461
Accuracy: 0.9516457435538695
1-10%
precision recall f1-score support
0 0.88 0.43 0.58 16949103
1 0.42 0.88 0.57 8016772
accuracy 0.57 24965875
macro avg 0.65 0.65 0.57 24965875
weighted avg 0.73 0.57 0.58 24965875
Accuracy: 0.5747385581318499
10-20%
precision recall f1-score support
0 0.45 0.03 0.05 2057494
1 0.73 0.99 0.84 5461156
accuracy 0.72 7518650
macro avg 0.59 0.51 0.44 7518650
weighted avg 0.65 0.72 0.62 7518650
Accuracy: 0.7249386525506574
20-40%
precision recall f1-score support
0 0.32 0.02 0.04 744974
1 0.85 0.99 0.91 4060539
accuracy 0.84 4805513
macro avg 0.58 0.51 0.48 4805513
weighted avg 0.76 0.84 0.78 4805513
Accuracy: 0.8415222266592557
40-80%
precision recall f1-score support
0 0.26 0.02 0.04 235909
1 0.91 0.99 0.95 2483775
accuracy 0.91 2719684
macro avg 0.59 0.51 0.50 2719684
weighted avg 0.86 0.91 0.87 2719684
Accuracy: 0.9094619080746146
80-90%
precision recall f1-score support
0 0.23 0.03 0.05 18577
1 0.94 0.99 0.97 296772
accuracy 0.94 315349
macro avg 0.59 0.51 0.51 315349
weighted avg 0.90 0.94 0.91 315349
Accuracy: 0.9372853568585916
90-100%
precision recall f1-score support
0 0.22 0.03 0.05 13620
1 0.95 0.99 0.97 240209
accuracy 0.94 253829
macro avg 0.58 0.51 0.51 253829
weighted avg 0.91 0.94 0.92 253829
Accuracy: 0.9423548924669758
Treshold: 0.5
All
precision recall f1-score support
0 0.84 0.65 0.73 24893266
1 0.66 0.85 0.74 20563095
accuracy 0.74 45456361
macro avg 0.75 0.75 0.74 45456361
weighted avg 0.76 0.74 0.74 45456361
Accuracy: 0.7366477048173742
precision recall f1-score support
0 0.84 0.65 0.73 24893266
1 0.66 0.85 0.74 20563095
accuracy 0.74 45456361
macro avg 0.75 0.75 0.74 45456361
weighted avg 0.76 0.74 0.74 45456361
Accuracy: 0.7366477048173742
0-1%
precision recall f1-score support
0 1.00 0.98 0.99 4873589
1 0.01 0.11 0.01 3872
accuracy 0.98 4877461
macro avg 0.50 0.55 0.50 4877461
weighted avg 1.00 0.98 0.99 4877461
Accuracy: 0.9834586068448318
1-10%
precision recall f1-score support
0 0.81 0.65 0.72 16949103
1 0.48 0.69 0.56 8016772
accuracy 0.66 24965875
macro avg 0.65 0.67 0.64 24965875
weighted avg 0.71 0.66 0.67 24965875
Accuracy: 0.6594332463813105
precision recall f1-score support
0 0.86 0.72 0.79 21822692
1 0.48 0.69 0.56 8020644
accuracy 0.71 29843336
macro avg 0.67 0.70 0.67 29843336
weighted avg 0.76 0.71 0.73 29843336
Accuracy: 0.7123905651834634
10-20%
precision recall f1-score support
0 0.85 0.67 0.75 23880186
1 0.57 0.79 0.66 13481800
accuracy 0.71 37361986
macro avg 0.71 0.73 0.71 37361986
weighted avg 0.75 0.71 0.72 37361986
Accuracy: 0.7124592895035077
precision recall f1-score support
0 0.42 0.13 0.19 2057494
1 0.74 0.93 0.83 5461156
accuracy 0.71 7518650
macro avg 0.58 0.53 0.51 7518650
weighted avg 0.65 0.71 0.65 7518650
Accuracy: 0.7127320729120254
20-40%
precision recall f1-score support
0 0.84 0.65 0.73 24625160
1 0.63 0.83 0.71 17542339
accuracy 0.72 42167499
macro avg 0.73 0.74 0.72 42167499
weighted avg 0.75 0.72 0.73 42167499
Accuracy: 0.7246990863745559
precision recall f1-score support
0 0.25 0.08 0.13 744974
1 0.85 0.96 0.90 4060539
accuracy 0.82 4805513
macro avg 0.55 0.52 0.51 4805513
weighted avg 0.76 0.82 0.78 4805513
Accuracy: 0.8198612718350777
40-80%
precision recall f1-score support
0 0.16 0.08 0.10 235909
1 0.92 0.96 0.94 2483775
accuracy 0.88 2719684
macro avg 0.54 0.52 0.52 2719684
weighted avg 0.85 0.88 0.87 2719684
Accuracy: 0.8848274284806618
precision recall f1-score support
0 0.84 0.65 0.73 24861069
1 0.66 0.84 0.74 20026114
accuracy 0.73 44887183
macro avg 0.75 0.74 0.73 44887183
weighted avg 0.76 0.73 0.73 44887183
Accuracy: 0.7344011541111858
80-90%
precision recall f1-score support
0 0.12 0.08 0.09 18577
1 0.94 0.96 0.95 296772
accuracy 0.91 315349
macro avg 0.53 0.52 0.52 315349
weighted avg 0.89 0.91 0.90 315349
Accuracy: 0.911764426080311
90-100%
precision recall f1-score support
0 0.10 0.07 0.09 13620
1 0.95 0.96 0.96 240209
accuracy 0.92 253829
macro avg 0.53 0.52 0.52 253829
weighted avg 0.90 0.92 0.91 253829
Accuracy: 0.9163767733395317
Treshold: 0.6
All
precision recall f1-score support
0 0.78 0.75 0.76 24893266
1 0.71 0.74 0.72 20563095
accuracy 0.74 45456361
macro avg 0.74 0.74 0.74 45456361
weighted avg 0.74 0.74 0.74 45456361
Accuracy: 0.7428775039867358
0-1%
precision recall f1-score support
0 1.00 0.99 1.00 4873589
1 0.01 0.07 0.02 3872
accuracy 0.99 4877461
macro avg 0.50 0.53 0.51 4877461
weighted avg 1.00 0.99 1.00 4877461
Accuracy: 0.9929239823752563
1-10%
precision recall f1-score support
0 0.77 0.77 0.77 16949103
1 0.51 0.52 0.52 8016772
accuracy 0.69 24965875
macro avg 0.64 0.64 0.64 24965875
weighted avg 0.69 0.69 0.69 24965875
Accuracy: 0.6878690612686317
10-20%
precision recall f1-score support
0 0.40 0.26 0.32 2057494
1 0.75 0.85 0.80 5461156
accuracy 0.69 7518650
macro avg 0.57 0.56 0.56 7518650
weighted avg 0.66 0.69 0.67 7518650
Accuracy: 0.6885870468767664
20-40%
precision recall f1-score support
0 0.24 0.18 0.20 744974
1 0.86 0.90 0.88 4060539
accuracy 0.79 4805513
macro avg 0.55 0.54 0.54 4805513
weighted avg 0.76 0.79 0.77 4805513
Accuracy: 0.7856116506187789
40-80%
precision recall f1-score support
0 0.14 0.15 0.15 235909
1 0.92 0.91 0.92 2483775
accuracy 0.85 2719684
macro avg 0.53 0.53 0.53 2719684
weighted avg 0.85 0.85 0.85 2719684
Accuracy: 0.8464549557963351
80-90%
precision recall f1-score support
0 0.10 0.15 0.12 18577
1 0.94 0.92 0.93 296772
accuracy 0.87 315349
macro avg 0.52 0.53 0.52 315349
weighted avg 0.90 0.87 0.88 315349
Accuracy: 0.872087750397179
90-100%
precision recall f1-score support
0 0.09 0.14 0.11 13620
1 0.95 0.92 0.93 240209
accuracy 0.88 253829
macro avg 0.52 0.53 0.52 253829
weighted avg 0.90 0.88 0.89 253829
Accuracy: 0.8773347411052322
Treshold: 0.7
All
precision recall f1-score support
0 0.70 0.86 0.77 24893266
1 0.76 0.54 0.63 20563095
accuracy 0.72 45456361
macro avg 0.73 0.70 0.70 45456361
weighted avg 0.73 0.72 0.71 45456361
Accuracy: 0.7165926018582965
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.02 0.03 0.03 3872
accuracy 1.00 4877461
macro avg 0.51 0.52 0.51 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9978864003218068
1-10%
precision recall f1-score support
0 0.73 0.89 0.80 16949103
1 0.56 0.29 0.38 8016772
accuracy 0.70 24965875
macro avg 0.64 0.59 0.59 24965875
weighted avg 0.67 0.70 0.67 24965875
Accuracy: 0.6978424349236708
10-20%
precision recall f1-score support
0 0.34 0.52 0.41 2057494
1 0.78 0.63 0.69 5461156
accuracy 0.60 7518650
macro avg 0.56 0.57 0.55 7518650
weighted avg 0.66 0.60 0.62 7518650
Accuracy: 0.5973688095602269
20-40%
precision recall f1-score support
0 0.22 0.38 0.28 744974
1 0.87 0.75 0.80 4060539
accuracy 0.69 4805513
macro avg 0.54 0.56 0.54 4805513
weighted avg 0.77 0.69 0.72 4805513
Accuracy: 0.6911805253674269
40-80%
precision recall f1-score support
0 0.13 0.33 0.19 235909
1 0.93 0.79 0.85 2483775
accuracy 0.75 2719684
macro avg 0.53 0.56 0.52 2719684
weighted avg 0.86 0.75 0.79 2719684
Accuracy: 0.7467948482250144
80-90%
precision recall f1-score support
0 0.09 0.31 0.14 18577
1 0.95 0.80 0.87 296772
accuracy 0.77 315349
macro avg 0.52 0.56 0.50 315349
weighted avg 0.90 0.77 0.82 315349
Accuracy: 0.770765088838081
90-100%
precision recall f1-score support
0 0.08 0.31 0.13 13620
1 0.95 0.80 0.87 240209
accuracy 0.78 253829
macro avg 0.52 0.56 0.50 253829
weighted avg 0.91 0.78 0.83 253829
Accuracy: 0.7773067695180613
Treshold: 0.8
All
precision recall f1-score support
0 0.59 0.97 0.73 24893266
1 0.83 0.17 0.28 20563095
accuracy 0.61 45456361
macro avg 0.71 0.57 0.50 45456361
weighted avg 0.69 0.61 0.53 45456361
Accuracy: 0.6076901976381259
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.00 0.01 3872
accuracy 1.00 4877461
macro avg 0.52 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991612439340878
1-10%
precision recall f1-score support
0 0.69 0.98 0.81 16949103
1 0.62 0.06 0.11 8016772
accuracy 0.69 24965875
macro avg 0.65 0.52 0.46 24965875
weighted avg 0.67 0.69 0.59 24965875
Accuracy: 0.6862799321073265
10-20%
precision recall f1-score support
0 0.28 0.90 0.43 2057494
1 0.79 0.15 0.25 5461156
accuracy 0.35 7518650
macro avg 0.54 0.52 0.34 7518650
weighted avg 0.66 0.35 0.30 7518650
Accuracy: 0.3530458260458992
20-40%
precision recall f1-score support
0 0.17 0.81 0.28 744974
1 0.88 0.26 0.40 4060539
accuracy 0.34 4805513
macro avg 0.52 0.53 0.34 4805513
weighted avg 0.77 0.34 0.38 4805513
Accuracy: 0.34364738998729166
40-80%
precision recall f1-score support
0 0.10 0.72 0.17 235909
1 0.93 0.36 0.52 2483775
accuracy 0.39 2719684
macro avg 0.51 0.54 0.35 2719684
weighted avg 0.86 0.39 0.49 2719684
Accuracy: 0.39280519354454413
80-90%
precision recall f1-score support
0 0.07 0.68 0.12 18577
1 0.95 0.41 0.57 296772
accuracy 0.42 315349
macro avg 0.51 0.54 0.35 315349
weighted avg 0.90 0.42 0.54 315349
Accuracy: 0.42275383781144066
90-100%
precision recall f1-score support
0 0.06 0.67 0.11 13620
1 0.96 0.42 0.58 240209
accuracy 0.43 253829
macro avg 0.51 0.54 0.35 253829
weighted avg 0.91 0.43 0.55 253829
Accuracy: 0.4293638630731713
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.00 0.00 0.00 20563095
accuracy 0.55 45456361
macro avg 0.27 0.50 0.35 45456361
weighted avg 0.30 0.55 0.39 45456361
Accuracy: 0.5476299785633962
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.00 0.00 0.00 3872
accuracy 1.00 4877461
macro avg 0.50 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9992061443443627
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.00 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.34 0.50 0.40 24965875
weighted avg 0.46 0.68 0.55 24965875
Accuracy: 0.678890805950122
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.00 0.00 0.00 5461156
accuracy 0.27 7518650
macro avg 0.14 0.50 0.21 7518650
weighted avg 0.07 0.27 0.12 7518650
Accuracy: 0.2736520518976146
20-40%
precision recall f1-score support
0 0.16 1.00 0.27 744974
1 0.00 0.00 0.00 4060539
accuracy 0.16 4805513
macro avg 0.08 0.50 0.13 4805513
weighted avg 0.02 0.16 0.04 4805513
Accuracy: 0.15502486415082012
40-80%
precision recall f1-score support
0 0.09 1.00 0.16 235909
1 0.00 0.00 0.00 2483775
accuracy 0.09 2719684
macro avg 0.04 0.50 0.08 2719684
weighted avg 0.01 0.09 0.01 2719684
Accuracy: 0.08674132730126
80-90%
precision recall f1-score support
0 0.06 1.00 0.11 18577
1 0.00 0.00 0.00 296772
accuracy 0.06 315349
macro avg 0.03 0.50 0.06 315349
weighted avg 0.00 0.06 0.01 315349
Accuracy: 0.05890933537128705
90-100%
precision recall f1-score support
0 0.05 1.00 0.10 13620
1 0.00 0.00 0.00 240209
accuracy 0.05 253829
macro avg 0.03 0.50 0.05 253829
weighted avg 0.00 0.05 0.01 253829
Accuracy: 0.05365817144613105
0.4
Treshold: 0.3
All
precision recall f1-score support
0 0.92 0.50 0.64 22531902
1 0.58 0.95 0.72 16938696
accuracy 0.69 39470598
macro avg 0.75 0.72 0.68 39470598
weighted avg 0.78 0.69 0.68 39470598
Accuracy: 0.6886203244247782
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999606451359001
1-10%
precision recall f1-score support
0 0.95 0.74 0.83 11439888
1 0.22 0.67 0.33 1271288
accuracy 0.73 12711176
macro avg 0.59 0.70 0.58 12711176
weighted avg 0.88 0.73 0.78 12711176
Accuracy: 0.7288902301407832
10-20%
precision recall f1-score support
0 0.78 0.19 0.30 5044441
1 0.46 0.93 0.62 3812372
accuracy 0.51 8856813
macro avg 0.62 0.56 0.46 8856813
weighted avg 0.65 0.51 0.44 8856813
Accuracy: 0.5068793932986956
20-40%
precision recall f1-score support
0 0.59 0.06 0.12 2995598
1 0.66 0.98 0.79 5583215
accuracy 0.66 8578813
macro avg 0.62 0.52 0.45 8578813
weighted avg 0.63 0.66 0.55 8578813
Accuracy: 0.6574943410003226
40-80%
precision recall f1-score support
0 0.41 0.05 0.08 1295061
1 0.80 0.98 0.88 5001564
accuracy 0.79 6296625
macro avg 0.60 0.51 0.48 6296625
weighted avg 0.72 0.79 0.72 6296625
Accuracy: 0.790120580469696
80-90%
precision recall f1-score support
0 0.33 0.05 0.08 117971
1 0.86 0.98 0.92 692761
accuracy 0.85 810732
macro avg 0.60 0.51 0.50 810732
weighted avg 0.78 0.85 0.80 810732
Accuracy: 0.8478708130430278
90-100%
precision recall f1-score support
0 0.32 0.05 0.08 88944
1 0.87 0.98 0.92 577496
accuracy 0.86 666440
macro avg 0.60 0.52 0.50 666440
weighted avg 0.80 0.86 0.81 666440
Accuracy: 0.8596722885781165
Treshold: 0.5
All
precision recall f1-score support
0 0.85 0.66 0.74 22531902
1 0.65 0.84 0.73 16938696
accuracy 0.74 39470598
macro avg 0.75 0.75 0.74 39470598
weighted avg 0.76 0.74 0.74 39470598
Accuracy: 0.7380526385741609
precision recall f1-score support
0 0.85 0.66 0.74 22531902
1 0.65 0.84 0.73 16938696
accuracy 0.74 39470598
macro avg 0.75 0.75 0.74 39470598
weighted avg 0.76 0.74 0.74 39470598
Accuracy: 0.7380526385741609
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999987096765869
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999987096765869
1-10%
precision recall f1-score support
0 0.94 0.89 0.91 12989887
1 0.27 0.42 0.33 1271288
accuracy 0.85 14261175
macro avg 0.61 0.65 0.62 14261175
weighted avg 0.88 0.85 0.86 14261175
Accuracy: 0.848054175059208
precision recall f1-score support
0 0.93 0.88 0.90 11439888
1 0.27 0.42 0.33 1271288
accuracy 0.83 12711176
macro avg 0.60 0.65 0.62 12711176
weighted avg 0.87 0.83 0.85 12711176
Accuracy: 0.8295260800416893
10-20%
precision recall f1-score support
0 0.89 0.77 0.83 18034328
1 0.46 0.68 0.54 5083660
accuracy 0.75 23117988
macro avg 0.68 0.72 0.69 23117988
weighted avg 0.80 0.75 0.77 23117988
Accuracy: 0.7512524446331575
precision recall f1-score support
0 0.72 0.47 0.57 5044441
1 0.52 0.76 0.62 3812372
accuracy 0.60 8856813
macro avg 0.62 0.62 0.59 8856813
weighted avg 0.64 0.60 0.59 8856813
Accuracy: 0.5953830119253958
20-40%
precision recall f1-score support
0 0.55 0.23 0.33 2995598
1 0.69 0.90 0.78 5583215
accuracy 0.67 8578813
macro avg 0.62 0.57 0.55 8578813
weighted avg 0.64 0.67 0.62 8578813
Accuracy: 0.6660222107650557
40-80%
precision recall f1-score support
0 0.85 0.66 0.75 22324987
1 0.64 0.83 0.72 15668439
accuracy 0.73 37993426
macro avg 0.74 0.75 0.73 37993426
weighted avg 0.76 0.73 0.74 37993426
Accuracy: 0.7347891185175035
precision recall f1-score support
0 0.36 0.17 0.23 1295061
1 0.81 0.92 0.86 5001564
accuracy 0.77 6296625
macro avg 0.59 0.55 0.55 6296625
weighted avg 0.72 0.77 0.73 6296625
Accuracy: 0.7680354157981458
80-90%
precision recall f1-score support
0 0.28 0.16 0.20 117971
1 0.87 0.93 0.90 692761
accuracy 0.82 810732
macro avg 0.57 0.54 0.55 810732
weighted avg 0.78 0.82 0.80 810732
Accuracy: 0.8174538565148532
90-100%
precision recall f1-score support
0 0.26 0.15 0.19 88944
1 0.88 0.93 0.90 577496
accuracy 0.83 666440
macro avg 0.57 0.54 0.55 666440
weighted avg 0.79 0.83 0.81 666440
Accuracy: 0.8275118540303703
Treshold: 0.6
All
precision recall f1-score support
0 0.79 0.76 0.77 22531902
1 0.69 0.74 0.72 16938696
accuracy 0.75 39470598
macro avg 0.74 0.75 0.74 39470598
weighted avg 0.75 0.75 0.75 39470598
Accuracy: 0.7480624945180714
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
1 0.00 0.00 0.00 0
accuracy 1.00 1549999
macro avg 0.50 0.50 0.50 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 0.9999993548382935
1-10%
precision recall f1-score support
0 0.92 0.93 0.92 11439888
1 0.31 0.30 0.30 1271288
accuracy 0.86 12711176
macro avg 0.62 0.61 0.61 12711176
weighted avg 0.86 0.86 0.86 12711176
Accuracy: 0.8637324351421143
10-20%
precision recall f1-score support
0 0.68 0.64 0.66 5044441
1 0.56 0.60 0.58 3812372
accuracy 0.63 8856813
macro avg 0.62 0.62 0.62 8856813
weighted avg 0.63 0.63 0.63 8856813
Accuracy: 0.6256777691930495
20-40%
precision recall f1-score support
0 0.52 0.40 0.45 2995598
1 0.71 0.80 0.76 5583215
accuracy 0.66 8578813
macro avg 0.62 0.60 0.60 8578813
weighted avg 0.65 0.66 0.65 8578813
Accuracy: 0.6613801932738247
40-80%
precision recall f1-score support
0 0.34 0.30 0.32 1295061
1 0.82 0.85 0.84 5001564
accuracy 0.74 6296625
macro avg 0.58 0.57 0.58 6296625
weighted avg 0.72 0.74 0.73 6296625
Accuracy: 0.7355694518889088
80-90%
precision recall f1-score support
0 0.25 0.28 0.27 117971
1 0.88 0.86 0.87 692761
accuracy 0.77 810732
macro avg 0.56 0.57 0.57 810732
weighted avg 0.78 0.77 0.78 810732
Accuracy: 0.7745901234933369
90-100%
precision recall f1-score support
0 0.24 0.27 0.25 88944
1 0.89 0.86 0.87 577496
accuracy 0.78 666440
macro avg 0.56 0.57 0.56 666440
weighted avg 0.80 0.78 0.79 666440
Accuracy: 0.783961046755897
Treshold: 0.7
All
precision recall f1-score support
0 0.72 0.86 0.78 22531902
1 0.75 0.55 0.64 16938696
accuracy 0.73 39470598
macro avg 0.74 0.71 0.71 39470598
weighted avg 0.73 0.73 0.72 39470598
Accuracy: 0.729504022209139
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.91 0.97 0.94 11439888
1 0.37 0.17 0.24 1271288
accuracy 0.89 12711176
macro avg 0.64 0.57 0.59 12711176
weighted avg 0.86 0.89 0.87 12711176
Accuracy: 0.8877047253535
10-20%
precision recall f1-score support
0 0.64 0.82 0.71 5044441
1 0.61 0.38 0.47 3812372
accuracy 0.63 8856813
macro avg 0.62 0.60 0.59 8856813
weighted avg 0.62 0.63 0.61 8856813
Accuracy: 0.6289582945919712
20-40%
precision recall f1-score support
0 0.46 0.64 0.54 2995598
1 0.76 0.60 0.67 5583215
accuracy 0.62 8578813
macro avg 0.61 0.62 0.60 8578813
weighted avg 0.65 0.62 0.62 8578813
Accuracy: 0.6154167249012189
40-80%
precision recall f1-score support
0 0.30 0.53 0.39 1295061
1 0.85 0.68 0.76 5001564
accuracy 0.65 6296625
macro avg 0.58 0.61 0.57 6296625
weighted avg 0.74 0.65 0.68 6296625
Accuracy: 0.6526744089095349
80-90%
precision recall f1-score support
0 0.22 0.50 0.31 117971
1 0.89 0.70 0.79 692761
accuracy 0.67 810732
macro avg 0.56 0.60 0.55 810732
weighted avg 0.79 0.67 0.72 810732
Accuracy: 0.673934173068289
90-100%
precision recall f1-score support
0 0.21 0.49 0.29 88944
1 0.90 0.71 0.79 577496
accuracy 0.68 666440
macro avg 0.55 0.60 0.54 666440
weighted avg 0.81 0.68 0.73 666440
Accuracy: 0.6813111457895684
Treshold: 0.8
All
precision recall f1-score support
0 0.62 0.96 0.76 22531902
1 0.82 0.23 0.36 16938696
accuracy 0.65 39470598
macro avg 0.72 0.60 0.56 39470598
weighted avg 0.71 0.65 0.59 39470598
Accuracy: 0.6486366130049511
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 0.99 0.95 11439888
1 0.47 0.06 0.10 1271288
accuracy 0.90 12711176
macro avg 0.69 0.52 0.52 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.8992405580726756
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.13 0.22 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.48 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5995083107207977
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.81 0.23 0.36 5583215
accuracy 0.47 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.66 0.47 0.43 8578813
Accuracy: 0.46689093234693424
40-80%
precision recall f1-score support
0 0.24 0.84 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.43 6296625
macro avg 0.56 0.58 0.42 6296625
weighted avg 0.75 0.43 0.45 6296625
Accuracy: 0.42760097671371566
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.42 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.42 0.47 810732
Accuracy: 0.41565770192862744
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.36 0.51 577496
accuracy 0.42 666440
macro avg 0.54 0.58 0.39 666440
weighted avg 0.82 0.42 0.48 666440
Accuracy: 0.4158483884520737
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.00 0.00 0.00 16938696
accuracy 0.57 39470598
macro avg 0.29 0.50 0.36 39470598
weighted avg 0.33 0.57 0.41 39470598
Accuracy: 0.5708528155565314
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 1.00 0.95 11439888
1 0.00 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.45 0.50 0.47 12711176
weighted avg 0.81 0.90 0.85 12711176
Accuracy: 0.8999865944740282
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.00 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.28 0.50 0.36 8856813
weighted avg 0.32 0.57 0.41 8856813
Accuracy: 0.5695548726161431
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.00 0.00 0.00 5583215
accuracy 0.35 8578813
macro avg 0.17 0.50 0.26 8578813
weighted avg 0.12 0.35 0.18 8578813
Accuracy: 0.34918560411562766
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.00 0.00 0.00 5001564
accuracy 0.21 6296625
macro avg 0.10 0.50 0.17 6296625
weighted avg 0.04 0.21 0.07 6296625
Accuracy: 0.20567542135667918
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.00 0.00 0.00 692761
accuracy 0.15 810732
macro avg 0.07 0.50 0.13 810732
weighted avg 0.02 0.15 0.04 810732
Accuracy: 0.14551171040491803
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.00 0.00 0.00 577496
accuracy 0.13 666440
macro avg 0.07 0.50 0.12 666440
weighted avg 0.02 0.13 0.03 666440
Accuracy: 0.13346137686813517
Individual Workload Result
zipf_1_15
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6046758 | 0.403719 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| Zipf Optimal Distribution | 9519768 | 0.404397 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9773902 | 0.404839 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9740182 | 0.404872 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9723106 | 0.404903 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10299939 | 0.405037 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10298833 | 0.405037 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10300318 | 0.40504 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| Offline Clock 1st iteration | 10440959 | 0.405173 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.7] | 7446464 | 0.409234 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.7] | 7439896 | 0.409298 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.7] | 7445242 | 0.409313 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.6] | 5624188 | 0.415091 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.6] | 5603042 | 0.415147 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.6] | 5577121 | 0.415205 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.5] | 4377254 | 0.420167 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.5] | 4370271 | 0.420208 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.5] | 4350655 | 0.420286 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.3] | 2828327 | 0.428148 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.3] | 2830034 | 0.428148 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.3] | 2833313 | 0.428156 | ../../result/log/zipf_1_15 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5855919 | 0.209857 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| Zipf Optimal Distribution | 8927244 | 0.211885 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9749804 | 0.213586 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9741455 | 0.213588 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9737587 | 0.213589 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| Offline Clock 1st iteration | 10273545 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10273489 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10273491 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10273491 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.7] | 7148453 | 0.216419 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.7] | 7146708 | 0.216428 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.7] | 7147423 | 0.216431 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.6] | 5362457 | 0.220694 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.6] | 5358127 | 0.220695 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.6] | 5360087 | 0.220696 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.5] | 4191256 | 0.224658 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.5] | 4189445 | 0.224661 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.5] | 4186743 | 0.224667 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.3] | 2724482 | 0.231276 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.3] | 2724487 | 0.231277 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.3] | 2723140 | 0.231285 | ../../result/log/zipf_1_15 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5679810 | 0.147307 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| Zipf Optimal Distribution | 8496578 | 0.150203 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| Offline Clock 1st iteration | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9531967 | 0.152768 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9531595 | 0.152769 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9517061 | 0.15277 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.7] | 7016918 | 0.154434 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.7] | 7014777 | 0.154437 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.7] | 7009169 | 0.154446 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.6] | 5229392 | 0.157674 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.6] | 5226757 | 0.157678 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.6] | 5227411 | 0.157682 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.5] | 4065657 | 0.160931 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.5] | 4064883 | 0.160932 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.5] | 4062785 | 0.160937 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.3] | 2617987 | 0.166683 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.3] | 2615867 | 0.166692 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.3] | 2614961 | 0.166696 | ../../result/log/zipf_1_15 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5220469 | 0.0827401 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| Zipf Optimal Distribution | 7658498 | 0.0867334 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| Offline Clock 1st iteration | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8605042 | 0.0898638 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8604425 | 0.0898642 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8604072 | 0.0898644 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.7] | 6564964 | 0.0906803 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.7] | 6564442 | 0.0906805 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.7] | 6564585 | 0.0906806 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.6] | 4885936 | 0.0923636 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.6] | 4886072 | 0.0923637 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.6] | 4886450 | 0.0923637 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.5] | 3740510 | 0.0943411 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.5] | 3740168 | 0.0943415 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.5] | 3740868 | 0.094342 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.3] | 2380282 | 0.0982626 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.3] | 2379947 | 0.0982632 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.3] | 2379664 | 0.0982641 | ../../result/log/zipf_1_15 | 0.4 | 1 |
zipf_1_16
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6044928 | 0.403882 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| Zipf Optimal Distribution | 9516893 | 0.40457 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9769605 | 0.405016 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9736498 | 0.405046 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9719385 | 0.405075 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10295691 | 0.405206 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10296736 | 0.405207 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10297041 | 0.405209 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| Offline Clock 1st iteration | 10437637 | 0.405347 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.7] | 7443136 | 0.409405 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.7] | 7436391 | 0.409469 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.7] | 7441925 | 0.409488 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.6] | 5622068 | 0.415253 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.6] | 5600263 | 0.415314 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.6] | 5574530 | 0.415374 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.5] | 4375097 | 0.420329 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.5] | 4368814 | 0.420365 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.5] | 4349191 | 0.420441 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.3] | 2830245 | 0.428275 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.3] | 2828400 | 0.428276 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.3] | 2833294 | 0.428283 | ../../result/log/zipf_1_16 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5851636 | 0.210029 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| Zipf Optimal Distribution | 8926367 | 0.212052 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9750736 | 0.213751 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9743143 | 0.213754 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9739734 | 0.213755 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| Offline Clock 1st iteration | 10274590 | 0.213983 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10274532 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10274534 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10274534 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.7] | 7151491 | 0.21657 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.7] | 7149477 | 0.216579 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.7] | 7150467 | 0.216582 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.6] | 5362692 | 0.220857 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.6] | 5358593 | 0.220859 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.6] | 5360305 | 0.22086 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.5] | 4190226 | 0.224816 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.5] | 4188394 | 0.224819 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.5] | 4185754 | 0.224825 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.3] | 2725171 | 0.231416 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.3] | 2725154 | 0.231417 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.3] | 2723740 | 0.231426 | ../../result/log/zipf_1_16 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5683642 | 0.147393 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| Zipf Optimal Distribution | 8505430 | 0.150288 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| Offline Clock 1st iteration | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9547859 | 0.152851 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9547489 | 0.152852 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9535780 | 0.152853 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.7] | 7023421 | 0.15454 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.7] | 7021371 | 0.154542 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.7] | 7015930 | 0.154551 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.6] | 5236734 | 0.157779 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.6] | 5233863 | 0.157783 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.6] | 5234636 | 0.157786 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.5] | 4067828 | 0.161033 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.5] | 4068538 | 0.161034 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.5] | 4065692 | 0.161038 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.3] | 2619181 | 0.166771 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.3] | 2617153 | 0.16678 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.3] | 2616355 | 0.166784 | ../../result/log/zipf_1_16 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5225924 | 0.0827439 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| Zipf Optimal Distribution | 7664562 | 0.0867505 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| Offline Clock 1st iteration | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8611294 | 0.0898878 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8610365 | 0.0898882 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8610028 | 0.0898884 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.7] | 6576404 | 0.0906925 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.7] | 6575676 | 0.0906927 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.7] | 6575861 | 0.0906929 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.6] | 4894579 | 0.0923771 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.6] | 4894969 | 0.0923773 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.6] | 4894672 | 0.0923775 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.5] | 3743350 | 0.0943692 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.5] | 3743079 | 0.0943696 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.5] | 3743751 | 0.0943697 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.3] | 2384703 | 0.098265 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.3] | 2384344 | 0.0982657 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.3] | 2384094 | 0.0982662 | ../../result/log/zipf_1_16 | 0.4 | 1 |
zipf_1_17
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6046350 | 0.403777 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| Zipf Optimal Distribution | 9518366 | 0.404457 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9771886 | 0.404899 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9738418 | 0.404932 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9721381 | 0.404961 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10298403 | 0.405097 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10297456 | 0.405097 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10298864 | 0.405099 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| Offline Clock 1st iteration | 10439561 | 0.405242 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.7] | 7446165 | 0.409288 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.7] | 7440328 | 0.409353 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.7] | 7445732 | 0.409371 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.6] | 5625900 | 0.41513 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.6] | 5604181 | 0.415189 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.6] | 5578573 | 0.415244 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.5] | 4377646 | 0.420218 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.5] | 4370959 | 0.420257 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.5] | 4351594 | 0.420333 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.3] | 2832383 | 0.428161 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.3] | 2830461 | 0.428163 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.3] | 2835421 | 0.428171 | ../../result/log/zipf_1_17 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5851791 | 0.209897 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| Zipf Optimal Distribution | 8925674 | 0.211925 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9747434 | 0.213628 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9739230 | 0.21363 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9735705 | 0.213631 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| Offline Clock 1st iteration | 10272630 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10272574 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10272576 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10272576 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.7] | 7146655 | 0.216453 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.7] | 7144703 | 0.216462 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.7] | 7145670 | 0.216464 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.6] | 5359842 | 0.220738 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.6] | 5356076 | 0.220739 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.6] | 5357644 | 0.220741 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.5] | 4189369 | 0.224683 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.5] | 4187519 | 0.224686 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.5] | 4184896 | 0.224693 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.3] | 2724773 | 0.231282 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.3] | 2724954 | 0.231283 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.3] | 2723549 | 0.231291 | ../../result/log/zipf_1_17 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5680729 | 0.147336 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| Zipf Optimal Distribution | 8498188 | 0.150231 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| Offline Clock 1st iteration | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9523014 | 0.152804 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9536570 | 0.152804 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9536275 | 0.152805 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.7] | 7018075 | 0.154471 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.7] | 7015849 | 0.154474 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.7] | 7010319 | 0.154484 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.6] | 5231447 | 0.157695 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.6] | 5227521 | 0.157699 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.6] | 5228704 | 0.157703 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.5] | 4064674 | 0.16096 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.5] | 4063819 | 0.16096 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.5] | 4061748 | 0.160965 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.3] | 2617155 | 0.16672 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.3] | 2615194 | 0.166728 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.3] | 2614227 | 0.166733 | ../../result/log/zipf_1_17 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5224778 | 0.0827112 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| Zipf Optimal Distribution | 7661751 | 0.0867151 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| Offline Clock 1st iteration | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8607827 | 0.0898513 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8608122 | 0.0898514 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8608694 | 0.0898514 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.7] | 6567879 | 0.0906525 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.7] | 6567706 | 0.0906527 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.7] | 6568329 | 0.0906528 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.6] | 4888938 | 0.0923504 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.6] | 4889390 | 0.0923506 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.6] | 4889127 | 0.0923508 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.5] | 3740101 | 0.0943324 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.5] | 3740335 | 0.0943325 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.5] | 3740741 | 0.0943328 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.3] | 2382480 | 0.0982436 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.3] | 2382153 | 0.0982441 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.3] | 2381894 | 0.098245 | ../../result/log/zipf_1_17 | 0.4 | 1 |
zipf_1_18
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6046061 | 0.40372 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| Zipf Optimal Distribution | 9518058 | 0.404413 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9772939 | 0.404858 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9739576 | 0.404889 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9722629 | 0.404917 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10299138 | 0.405058 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10298097 | 0.405058 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10299781 | 0.405059 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| Offline Clock 1st iteration | 10439737 | 0.4052 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.7] | 7448289 | 0.409229 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.7] | 7441892 | 0.409297 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.7] | 7447352 | 0.409313 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.6] | 5625647 | 0.415084 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.6] | 5603976 | 0.415143 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.6] | 5577903 | 0.4152 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.5] | 4377907 | 0.420158 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.5] | 4371182 | 0.420198 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.5] | 4351494 | 0.420276 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.3] | 2829302 | 0.428127 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.3] | 2830516 | 0.428127 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.3] | 2833644 | 0.428137 | ../../result/log/zipf_1_18 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5852167 | 0.209865 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| Zipf Optimal Distribution | 8924501 | 0.211883 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9741672 | 0.213594 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9733356 | 0.213597 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9730334 | 0.213597 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| Offline Clock 1st iteration | 10268394 | 0.213821 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10268336 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10268337 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10268339 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.7] | 7147408 | 0.216413 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.7] | 7145387 | 0.216423 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.7] | 7146208 | 0.216425 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.6] | 5363327 | 0.220687 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.6] | 5359661 | 0.220687 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.6] | 5361294 | 0.220688 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.5] | 4191256 | 0.224647 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.5] | 4189562 | 0.22465 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.5] | 4186886 | 0.224658 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.3] | 2726028 | 0.231245 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.3] | 2725888 | 0.231245 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.3] | 2724475 | 0.231254 | ../../result/log/zipf_1_18 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5677502 | 0.147262 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| Zipf Optimal Distribution | 8501025 | 0.150135 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| Offline Clock 1st iteration | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9518277 | 0.152725 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9531160 | 0.152725 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9530717 | 0.152726 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.7] | 7019488 | 0.154386 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.7] | 7017240 | 0.154388 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.7] | 7011633 | 0.1544 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.6] | 5230219 | 0.157625 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.6] | 5227751 | 0.157629 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.6] | 5228225 | 0.157633 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.5] | 4064793 | 0.160884 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.5] | 4064000 | 0.160885 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.5] | 4061832 | 0.160891 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.3] | 2616633 | 0.16663 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.3] | 2614507 | 0.166639 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.3] | 2613531 | 0.166644 | ../../result/log/zipf_1_18 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5223361 | 0.0826611 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| Zipf Optimal Distribution | 7661309 | 0.0866641 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| Offline Clock 1st iteration | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8606890 | 0.0897961 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8606269 | 0.0897963 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8605948 | 0.0897965 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.7] | 6559790 | 0.0906075 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.7] | 6559302 | 0.0906081 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.7] | 6558997 | 0.0906083 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.6] | 4884896 | 0.0922985 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.6] | 4884998 | 0.0922988 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.6] | 4885257 | 0.0922992 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.5] | 3738067 | 0.0942871 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.5] | 3737695 | 0.0942873 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.5] | 3737406 | 0.0942873 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.3] | 2379447 | 0.0982088 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.3] | 2379087 | 0.0982092 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.3] | 2378793 | 0.09821 | ../../result/log/zipf_1_18 | 0.4 | 1 |
zipf_1_19
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6047379 | 0.403776 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| Zipf Optimal Distribution | 9518278 | 0.404475 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9774585 | 0.404917 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9740851 | 0.404951 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9724440 | 0.404975 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10302179 | 0.405117 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10300967 | 0.405117 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10302521 | 0.405119 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| Offline Clock 1st iteration | 10442800 | 0.405256 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.7] | 7449074 | 0.409285 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.7] | 7441699 | 0.409355 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.7] | 7447270 | 0.409369 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.6] | 5626394 | 0.415125 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.6] | 5605240 | 0.415182 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.6] | 5578484 | 0.415245 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.5] | 4379187 | 0.420192 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.5] | 4372916 | 0.420231 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.5] | 4352719 | 0.420313 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.3] | 2830825 | 0.428173 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.3] | 2829026 | 0.428175 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.3] | 2833220 | 0.428188 | ../../result/log/zipf_1_19 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5852464 | 0.209927 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| Zipf Optimal Distribution | 8923837 | 0.21197 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9745686 | 0.213665 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9737676 | 0.213668 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9734226 | 0.213668 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| Offline Clock 1st iteration | 10270642 | 0.213882 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10270587 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10270590 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10270589 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.7] | 7147789 | 0.216477 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.7] | 7146054 | 0.216485 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.7] | 7147145 | 0.216487 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.6] | 5361338 | 0.220758 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.6] | 5359165 | 0.220761 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.6] | 5357160 | 0.220761 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.5] | 4189747 | 0.224721 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.5] | 4187890 | 0.224725 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.5] | 4185335 | 0.224731 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.3] | 2726451 | 0.231308 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.3] | 2726410 | 0.231308 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.3] | 2725232 | 0.231315 | ../../result/log/zipf_1_19 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5678610 | 0.147359 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| Zipf Optimal Distribution | 8501803 | 0.150225 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| Offline Clock 1st iteration | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9527439 | 0.152809 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9540045 | 0.15281 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9539643 | 0.152811 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.7] | 7018961 | 0.154486 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.7] | 7016787 | 0.154489 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.7] | 7011377 | 0.154498 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.6] | 5231219 | 0.157735 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.6] | 5228001 | 0.15774 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.6] | 5228702 | 0.157744 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.5] | 4063624 | 0.16099 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.5] | 4062831 | 0.160991 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.5] | 4060749 | 0.160996 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.3] | 2617038 | 0.166725 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.3] | 2614883 | 0.166734 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.3] | 2613982 | 0.166738 | ../../result/log/zipf_1_19 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5227240 | 0.0827181 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| Zipf Optimal Distribution | 7662557 | 0.0867323 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| Offline Clock 1st iteration | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8613404 | 0.0898297 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8612504 | 0.0898298 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8612834 | 0.0898298 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.7] | 6570367 | 0.0906611 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.7] | 6571009 | 0.0906615 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.7] | 6570572 | 0.0906615 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.6] | 4891710 | 0.0923776 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.6] | 4891576 | 0.0923777 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.6] | 4892065 | 0.0923778 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.5] | 3742627 | 0.0943506 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.5] | 3742200 | 0.0943506 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.5] | 3741938 | 0.094351 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.3] | 2383206 | 0.098261 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.3] | 2382856 | 0.0982613 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.3] | 2382602 | 0.098262 | ../../result/log/zipf_1_19 | 0.4 | 1 |