Zipf1 Current Best Models Test Data Result Obj Size Ignored
Result
Model Summaries
| Model | Better than base % of the times |
|---|
| 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_w_0_5[cache_size=0.01,treshold=0.6] | 100 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 100 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 100 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 0 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 100 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 100 |
| 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_w_0_5[cache_size=0.1,treshold=0.6] | 40 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 100 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 0 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 0 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 100 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 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_w_0_5[cache_size=0.2,treshold=0.6] | 100 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 100 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 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_w_0_5[cache_size=0.4,treshold=0.6] | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 20 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 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=0.6] | 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_w_0_5[cache_size=0.01,treshold=0.6] | 8.99214 | 8.96998 | 8.98099 | 8.98582 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 2.98432 | 2.96627 | 2.97332 | 2.97224 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 1.27474 | 1.26928 | 1.27208 | 1.27255 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 24.9419 | 24.9275 | 24.935 | 24.937 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 7.43222 | 7.41796 | 7.42725 | 7.42859 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 2.26341 | 2.25372 | 2.25761 | 2.2573 |
| 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_w_0_5[cache_size=0.1,treshold=0.6] | 11.2041 | 11.1792 | 11.1922 | 11.1894 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 0.0680096 | 0.0653948 | 0.0667291 | 0.0667113 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 0.000953906 | 0.000905494 | 0.00092874 | 0.000925169 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 29.4669 | 29.4313 | 29.4509 | 29.4519 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 8.79403 | 8.77334 | 8.78646 | 8.78731 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 0.00169452 | 0.00140205 | 0.00154402 | 0.00148926 |
| 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_w_0_5[cache_size=0.2,treshold=0.6] | 10.4566 | 10.3949 | 10.4257 | 10.4256 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 | 0 | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 | 0 | 0 | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 28.803 | 28.7651 | 28.7917 | 28.7981 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 8.03817 | 7.99152 | 8.01782 | 8.02019 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 0 | 0 | 0 | 0 |
| 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_w_0_5[cache_size=0.4,treshold=0.6] | 7.55555 | 7.52466 | 7.54661 | 7.55269 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 0.00235913 | 0.00129949 | 0.00168828 | 0.00139621 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 | 0 | 0 | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | 23.4619 | 23.3617 | 23.4114 | 23.4125 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 6.06344 | 5.99027 | 6.02358 | 6.02036 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 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=0.6] | -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_w_0_5[cache_size=0.01,treshold=0.6] | 0.0241856 | 0.0214631 | 0.0232454 | 0.0236887 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 0.0678677 | 0.0651574 | 0.0661331 | 0.066131 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 0.0333134 | 0.0313446 | 0.0323756 | 0.0320785 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | -0.760859 | -0.766833 | -0.763343 | -0.762754 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 0.0629232 | 0.060442 | 0.0618887 | 0.0626786 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 0.0540474 | 0.0518297 | 0.0531039 | 0.0530529 |
| 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_w_0_5[cache_size=0.1,treshold=0.6] | 0.00654766 | -0.00280568 | 0.000281158 | -0.00186931 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 0.00514449 | 0.00374152 | 0.00430168 | 0.00420793 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | -0.000467327 | -0.00046769 | -0.000467572 | -0.000467613 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | -1.11457 | -1.11965 | -1.11694 | -1.11589 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 0.067815 | 0.0570408 | 0.0611589 | 0.0598178 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | -0.000467327 | -0.00046769 | -0.000467572 | -0.000467613 |
| 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_w_0_5[cache_size=0.2,treshold=0.6] | 0.0307622 | 0.0189746 | 0.0244808 | 0.0242296 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 | 0 | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 | 0 | 0 | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | -0.95936 | -0.979481 | -0.969407 | -0.968903 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 0.0235625 | 0.0117773 | 0.0166259 | 0.0144068 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 0 | 0 | 0 | 0 |
| 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_w_0_5[cache_size=0.4,treshold=0.6] | -0.123575 | -0.15138 | -0.141567 | -0.146451 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 0.000111539 | -0.000334419 | -0.000133728 | -0.000111479 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 | 0 | 0 | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | -0.668127 | -0.711532 | -0.692896 | -0.701873 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | -0.110649 | -0.13697 | -0.125092 | -0.127636 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 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_7[cache_size=0.1,treshold=0.8] | 5.18877 | 0.104549 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.87683 | 0.0684527 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 2.97332 | 0.0661331 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 7.42725 | 0.0618887 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 8.78646 | 0.0611589 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 2.25761 | 0.0531039 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 1.27208 | 0.0323756 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.6] | 10.4257 | 0.0244808 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 8.98099 | 0.0232454 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 8.01782 | 0.0166259 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 0.0667291 | 0.00430168 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 11.1922 | 0.000281158 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 0.00168828 | -0.000133728 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 0.00092874 | -0.000467572 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 0.00154402 | -0.000467572 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.65984 | -0.0117823 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 6.02358 | -0.125092 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 7.54661 | -0.141567 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.83317 | -0.150485 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | 23.4114 | -0.692896 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 24.935 | -0.763343 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 28.7917 | -0.969407 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.6839 | -1.01845 |
| 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_7_w_0_75[cache_size=0.1,treshold=0.6] | 29.4509 | -1.11694 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4274 | -1.21774 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1229 | -2.44125 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.084 | -2.9458 |
| 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 |
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_7[cache_size=0.01,treshold=0.8] | 6.87683 | 0.0684527 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 2.97332 | 0.0661331 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 7.42725 | 0.0618887 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 2.25761 | 0.0531039 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 1.27208 | 0.0323756 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 8.98099 | 0.0232454 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 24.935 | -0.763343 |
| 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 |
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_7[cache_size=0.1,treshold=0.8] | 5.18877 | 0.104549 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 8.78646 | 0.0611589 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 0.0667291 | 0.00430168 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 11.1922 | 0.000281158 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 0.00092874 | -0.000467572 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 0.00154402 | -0.000467572 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 29.4509 | -1.11694 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4274 | -1.21774 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.822 | -3.21605 |
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_w_0_5[cache_size=0.2,treshold=0.6] | 10.4257 | 0.0244808 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 8.01782 | 0.0166259 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.65984 | -0.0117823 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 28.7917 | -0.969407 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8321 | -1.10608 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7012 | -3.22569 |
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 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 0.00168828 | -0.000133728 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 6.02358 | -0.125092 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 7.54661 | -0.141567 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.83317 | -0.150485 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | 23.4114 | -0.692896 |
| LR_7[cache_size=0.4,treshold=0.7] | 28.9199 | -1.05688 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.084 | -2.9458 |
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_7[cache_size=0.1,treshold=0.8] | 5.18922 | 0.104761 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.879 | 0.0693389 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 2.97224 | 0.066131 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 7.42859 | 0.0626786 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 8.78731 | 0.0598178 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 2.2573 | 0.0530529 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 1.27255 | 0.0320785 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.6] | 10.4256 | 0.0242296 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 8.98582 | 0.0236887 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 8.02019 | 0.0144068 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 0.0667113 | 0.00420793 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 0.00139621 | -0.000111479 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 0.00148926 | -0.000467613 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 0.000925169 | -0.000467613 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 11.1894 | -0.00186931 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.66176 | -0.0124353 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 6.02036 | -0.127636 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 7.55269 | -0.146451 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.84329 | -0.157828 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | 23.4125 | -0.701873 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 24.937 | -0.762754 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 28.7981 | -0.968903 |
| LR_7[cache_size=0.01,treshold=0.7] | 28.6851 | -1.0189 |
| 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_7_w_0_75[cache_size=0.1,treshold=0.6] | 29.4519 | -1.11589 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4225 | -1.21703 |
| LR_7[cache_size=0.01,treshold=0.6] | 46.1218 | -2.44002 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.0885 | -2.94612 |
| 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 |
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_7[cache_size=0.01,treshold=0.8] | 6.879 | 0.0693389 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 2.97224 | 0.066131 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 7.42859 | 0.0626786 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 2.2573 | 0.0530529 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 1.27255 | 0.0320785 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 8.98582 | 0.0236887 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 24.937 | -0.762754 |
| 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 |
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_7[cache_size=0.1,treshold=0.8] | 5.18922 | 0.104761 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 8.78731 | 0.0598178 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 0.0667113 | 0.00420793 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 0.00148926 | -0.000467613 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 0.000925169 | -0.000467613 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 11.1894 | -0.00186931 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 29.4519 | -1.11589 |
| LR_7[cache_size=0.1,treshold=0.7] | 30.4225 | -1.21703 |
| LR_7[cache_size=0.1,treshold=0.6] | 47.8263 | -3.21626 |
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_w_0_5[cache_size=0.2,treshold=0.6] | 10.4256 | 0.0242296 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 8.02019 | 0.0144068 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.66176 | -0.0124353 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 28.7981 | -0.968903 |
| LR_7[cache_size=0.2,treshold=0.7] | 29.8348 | -1.10351 |
| LR_7[cache_size=0.2,treshold=0.6] | 47.7035 | -3.22357 |
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 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 0 | 0 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 0.00139621 | -0.000111479 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 6.02036 | -0.127636 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 7.55269 | -0.146451 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.84329 | -0.157828 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.6] | 23.4125 | -0.701873 |
| LR_7[cache_size=0.4,treshold=0.7] | 28.9118 | -1.0552 |
| LR_7[cache_size=0.4,treshold=0.6] | 47.0885 | -2.94612 |
Model Classification Report
LR_7
0.01
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
0.1
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
0.2
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
0.4
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
LR_7_w_0_5
0.01
Treshold: 0.6
All
precision recall f1-score support
0 0.61 0.98 0.75 28055468
1 0.88 0.19 0.32 21729815
accuracy 0.64 49785283
macro avg 0.74 0.59 0.54 49785283
weighted avg 0.73 0.64 0.56 49785283
Accuracy: 0.6364741162564045
0-1%
precision recall f1-score support
0 0.63 0.98 0.77 27764588
1 0.76 0.08 0.14 17098553
accuracy 0.64 44863141
macro avg 0.70 0.53 0.46 44863141
weighted avg 0.68 0.64 0.53 44863141
Accuracy: 0.6395564010999587
1-10%
precision recall f1-score support
0 0.08 0.47 0.13 287564
1 0.94 0.60 0.73 4164787
accuracy 0.59 4452351
macro avg 0.51 0.54 0.43 4452351
weighted avg 0.89 0.59 0.70 4452351
Accuracy: 0.5933269861248586
10-20%
precision recall f1-score support
0 0.01 0.19 0.02 2455
1 0.99 0.81 0.89 257616
accuracy 0.81 260071
macro avg 0.50 0.50 0.46 260071
weighted avg 0.98 0.81 0.88 260071
Accuracy: 0.8064028669094209
20-40%
precision recall f1-score support
0 0.01 0.29 0.01 659
1 1.00 0.73 0.85 130568
accuracy 0.73 131227
macro avg 0.50 0.51 0.43 131227
weighted avg 0.99 0.73 0.84 131227
Accuracy: 0.732509315918218
40-80%
precision recall f1-score support
0 0.00 0.41 0.01 169
1 1.00 0.61 0.76 65234
accuracy 0.61 65403
macro avg 0.50 0.51 0.38 65403
weighted avg 0.99 0.61 0.76 65403
Accuracy: 0.612907664786019
80-90%
precision recall f1-score support
0 0.00 0.33 0.00 15
1 1.00 0.53 0.69 7371
accuracy 0.53 7386
macro avg 0.50 0.43 0.35 7386
weighted avg 1.00 0.53 0.69 7386
Accuracy: 0.5258597346330897
90-100%
precision recall f1-score support
0 0.00 0.50 0.01 18
1 1.00 0.53 0.69 5686
accuracy 0.53 5704
macro avg 0.50 0.51 0.35 5704
weighted avg 0.99 0.53 0.69 5704
Accuracy: 0.5291023842917251
Treshold: 0.7
All
precision recall f1-score support
0 0.58 1.00 0.73 28055468
1 0.94 0.07 0.13 21729815
accuracy 0.59 49785283
macro avg 0.76 0.53 0.43 49785283
weighted avg 0.74 0.59 0.47 49785283
Accuracy: 0.5915591762328638
0-1%
precision recall f1-score support
0 0.62 1.00 0.77 27764588
1 0.79 0.01 0.01 17098553
accuracy 0.62 44863141
macro avg 0.70 0.50 0.39 44863141
weighted avg 0.68 0.62 0.48 44863141
Accuracy: 0.6205877559932774
1-10%
precision recall f1-score support
0 0.07 0.80 0.13 287564
1 0.95 0.28 0.44 4164787
accuracy 0.32 4452351
macro avg 0.51 0.54 0.28 4452351
weighted avg 0.90 0.32 0.42 4452351
Accuracy: 0.3166715741863119
10-20%
precision recall f1-score support
0 0.01 0.44 0.02 2455
1 0.99 0.55 0.71 257616
accuracy 0.55 260071
macro avg 0.50 0.50 0.36 260071
weighted avg 0.98 0.55 0.70 260071
Accuracy: 0.5490539122008989
20-40%
precision recall f1-score support
0 0.00 0.61 0.01 659
1 0.99 0.36 0.53 130568
accuracy 0.36 131227
macro avg 0.50 0.49 0.27 131227
weighted avg 0.99 0.36 0.53 131227
Accuracy: 0.36371326022845907
40-80%
precision recall f1-score support
0 0.00 0.82 0.00 169
1 1.00 0.13 0.23 65234
accuracy 0.13 65403
macro avg 0.50 0.48 0.12 65403
weighted avg 0.99 0.13 0.23 65403
Accuracy: 0.1306209195296852
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 1.00 0.03 0.06 7371
accuracy 0.03 7386
macro avg 0.50 0.52 0.03 7386
weighted avg 1.00 0.03 0.06 7386
Accuracy: 0.034930950446791224
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 1.00 0.03 0.05 5686
accuracy 0.03 5704
macro avg 0.50 0.51 0.03 5704
weighted avg 1.00 0.03 0.05 5704
Accuracy: 0.029628330995792426
Treshold: 0.8
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 0.43 49785283
Accuracy: 0.5754383077424708
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.50 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.56 0.50 0.38 44863141
weighted avg 0.57 0.62 0.47 44863141
Accuracy: 0.618872896126466
1-10%
precision recall f1-score support
0 0.07 0.93 0.13 287564
1 0.96 0.13 0.23 4164787
accuracy 0.18 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.18 0.22 4452351
Accuracy: 0.17925136630063532
10-20%
precision recall f1-score support
0 0.01 0.70 0.02 2455
1 0.99 0.29 0.45 257616
accuracy 0.29 260071
macro avg 0.50 0.50 0.23 260071
weighted avg 0.98 0.29 0.44 260071
Accuracy: 0.29103975452857106
20-40%
precision recall f1-score support
0 0.00 0.92 0.01 659
1 0.99 0.07 0.13 130568
accuracy 0.07 131227
macro avg 0.50 0.49 0.07 131227
weighted avg 0.99 0.07 0.13 131227
Accuracy: 0.07416156736037553
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: 0.0035319480757763405
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: 0.6
All
precision recall f1-score support
0 0.61 0.95 0.74 26119367
1 0.83 0.26 0.39 21615229
accuracy 0.64 47734596
macro avg 0.72 0.61 0.57 47734596
weighted avg 0.71 0.64 0.58 47734596
Accuracy: 0.6390852454266084
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.22 0.02 0.04 508421
accuracy 0.96 12561431
macro avg 0.59 0.51 0.51 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9574953681630699
1-10%
precision recall f1-score support
0 0.50 0.94 0.65 13368467
1 0.71 0.14 0.24 14466820
accuracy 0.52 27835287
macro avg 0.61 0.54 0.45 27835287
weighted avg 0.61 0.52 0.44 27835287
Accuracy: 0.524072124709905
10-20%
precision recall f1-score support
0 0.14 0.60 0.23 503365
1 0.89 0.46 0.61 3387274
accuracy 0.48 3890639
macro avg 0.51 0.53 0.42 3890639
weighted avg 0.79 0.48 0.56 3890639
Accuracy: 0.4789030799310859
20-40%
precision recall f1-score support
0 0.08 0.47 0.13 147488
1 0.94 0.58 0.72 1970425
accuracy 0.58 2117913
macro avg 0.51 0.53 0.43 2117913
weighted avg 0.88 0.58 0.68 2117913
Accuracy: 0.5766459717656013
40-80%
precision recall f1-score support
0 0.04 0.44 0.08 41616
1 0.97 0.61 0.75 1064279
accuracy 0.61 1105895
macro avg 0.50 0.53 0.41 1105895
weighted avg 0.93 0.61 0.73 1105895
Accuracy: 0.6071516735313931
80-90%
precision recall f1-score support
0 0.03 0.45 0.05 3093
1 0.98 0.61 0.75 120943
accuracy 0.61 124036
macro avg 0.50 0.53 0.40 124036
weighted avg 0.95 0.61 0.73 124036
Accuracy: 0.6069689444999838
90-100%
precision recall f1-score support
0 0.03 0.44 0.05 2328
1 0.98 0.61 0.75 97067
accuracy 0.60 99395
macro avg 0.50 0.52 0.40 99395
weighted avg 0.96 0.60 0.73 99395
Accuracy: 0.6037426429900901
Treshold: 0.7
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.92 0.01 0.01 21615229
accuracy 0.55 47734596
macro avg 0.74 0.50 0.36 47734596
weighted avg 0.72 0.55 0.39 47734596
Accuracy: 0.5498496310726082
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: 0.959470620823376
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.80 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.64 0.50 0.32 27835287
weighted avg 0.64 0.48 0.31 27835287
Accuracy: 0.4803568937514458
10-20%
precision recall f1-score support
0 0.13 0.99 0.23 503365
1 0.89 0.01 0.02 3387274
accuracy 0.14 3890639
macro avg 0.51 0.50 0.12 3890639
weighted avg 0.79 0.14 0.05 3890639
Accuracy: 0.13679475273856043
20-40%
precision recall f1-score support
0 0.07 0.97 0.13 147488
1 0.93 0.03 0.07 1970425
accuracy 0.10 2117913
macro avg 0.50 0.50 0.10 2117913
weighted avg 0.87 0.10 0.07 2117913
Accuracy: 0.09932844266974139
40-80%
precision recall f1-score support
0 0.04 0.97 0.07 41616
1 0.96 0.03 0.06 1064279
accuracy 0.07 1105895
macro avg 0.50 0.50 0.07 1105895
weighted avg 0.93 0.07 0.06 1105895
Accuracy: 0.06571781226970011
80-90%
precision recall f1-score support
0 0.02 0.99 0.05 3093
1 0.98 0.02 0.03 120943
accuracy 0.04 124036
macro avg 0.50 0.50 0.04 124036
weighted avg 0.95 0.04 0.03 124036
Accuracy: 0.03958528169241188
90-100%
precision recall f1-score support
0 0.02 0.99 0.05 2328
1 0.98 0.01 0.02 97067
accuracy 0.04 99395
macro avg 0.50 0.50 0.03 99395
weighted avg 0.96 0.04 0.02 99395
Accuracy: 0.03500176065194426
Treshold: 0.8
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: 0.54716734169071
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: 0.9594810495715018
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: 0.6
All
precision recall f1-score support
0 0.61 0.95 0.74 24893266
1 0.82 0.27 0.41 20563095
accuracy 0.64 45456361
macro avg 0.71 0.61 0.58 45456361
weighted avg 0.70 0.64 0.59 45456361
Accuracy: 0.6433317660426007
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.01 0.02 3872
accuracy 1.00 4877461
macro avg 0.52 0.50 0.51 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9990613969030199
1-10%
precision recall f1-score support
0 0.69 0.97 0.81 16949103
1 0.60 0.10 0.17 8016772
accuracy 0.69 24965875
macro avg 0.65 0.53 0.49 24965875
weighted avg 0.66 0.69 0.60 24965875
Accuracy: 0.6898538905606152
10-20%
precision recall f1-score support
0 0.29 0.82 0.43 2057494
1 0.79 0.25 0.39 5461156
accuracy 0.41 7518650
macro avg 0.54 0.54 0.41 7518650
weighted avg 0.65 0.41 0.40 7518650
Accuracy: 0.40979590750999184
20-40%
precision recall f1-score support
0 0.18 0.66 0.28 744974
1 0.88 0.44 0.58 4060539
accuracy 0.47 4805513
macro avg 0.53 0.55 0.43 4805513
weighted avg 0.77 0.47 0.54 4805513
Accuracy: 0.47243322409074745
40-80%
precision recall f1-score support
0 0.10 0.57 0.18 235909
1 0.93 0.54 0.68 2483775
accuracy 0.54 2719684
macro avg 0.52 0.55 0.43 2719684
weighted avg 0.86 0.54 0.64 2719684
Accuracy: 0.5416662376952617
80-90%
precision recall f1-score support
0 0.07 0.54 0.13 18577
1 0.95 0.57 0.71 296772
accuracy 0.57 315349
macro avg 0.51 0.55 0.42 315349
weighted avg 0.90 0.57 0.68 315349
Accuracy: 0.5660331886259351
90-100%
precision recall f1-score support
0 0.07 0.53 0.12 13620
1 0.96 0.57 0.72 240209
accuracy 0.57 253829
macro avg 0.51 0.55 0.42 253829
weighted avg 0.91 0.57 0.68 253829
Accuracy: 0.5703721796957795
Treshold: 0.7
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.85 0.01 0.01 20563095
accuracy 0.55 45456361
macro avg 0.70 0.50 0.36 45456361
weighted avg 0.69 0.55 0.39 45456361
Accuracy: 0.5496577695693678
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: 0.9992057342949539
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.57 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.62 0.50 0.41 24965875
weighted avg 0.64 0.68 0.55 24965875
Accuracy: 0.678973919399981
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.78 0.00 0.01 5461156
accuracy 0.28 7518650
macro avg 0.53 0.50 0.22 7518650
weighted avg 0.64 0.28 0.12 7518650
Accuracy: 0.27544559196132284
20-40%
precision recall f1-score support
0 0.16 0.99 0.27 744974
1 0.88 0.01 0.02 4060539
accuracy 0.16 4805513
macro avg 0.52 0.50 0.14 4805513
weighted avg 0.76 0.16 0.05 4805513
Accuracy: 0.1605220920222253
40-80%
precision recall f1-score support
0 0.09 0.99 0.16 235909
1 0.94 0.02 0.03 2483775
accuracy 0.10 2719684
macro avg 0.51 0.50 0.10 2719684
weighted avg 0.86 0.10 0.04 2719684
Accuracy: 0.10034474593371877
80-90%
precision recall f1-score support
0 0.06 0.98 0.11 18577
1 0.95 0.02 0.05 296772
accuracy 0.08 315349
macro avg 0.51 0.50 0.08 315349
weighted avg 0.90 0.08 0.05 315349
Accuracy: 0.08098012043799092
90-100%
precision recall f1-score support
0 0.05 0.98 0.10 13620
1 0.96 0.03 0.05 240209
accuracy 0.08 253829
macro avg 0.51 0.50 0.08 253829
weighted avg 0.91 0.08 0.06 253829
Accuracy: 0.07825740951585516
Treshold: 0.8
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: 0.6
All
precision recall f1-score support
0 0.63 0.96 0.76 22531902
1 0.82 0.26 0.39 16938696
accuracy 0.66 39470598
macro avg 0.72 0.61 0.58 39470598
weighted avg 0.71 0.66 0.60 39470598
Accuracy: 0.6569262517887365
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 0.46 0.06 0.11 1271288
accuracy 0.90 12711176
macro avg 0.68 0.53 0.53 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.8990318441031735
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.14 0.24 3812372
accuracy 0.60 8856813
macro avg 0.64 0.55 0.48 8856813
weighted avg 0.63 0.60 0.52 8856813
Accuracy: 0.6020663414706847
20-40%
precision recall f1-score support
0 0.39 0.89 0.54 2995598
1 0.81 0.26 0.39 5583215
accuracy 0.48 8578813
macro avg 0.60 0.57 0.47 8578813
weighted avg 0.66 0.48 0.45 8578813
Accuracy: 0.47924951855227527
40-80%
precision recall f1-score support
0 0.25 0.82 0.38 1295061
1 0.88 0.36 0.51 5001564
accuracy 0.45 6296625
macro avg 0.57 0.59 0.44 6296625
weighted avg 0.75 0.45 0.48 6296625
Accuracy: 0.4521333253925714
80-90%
precision recall f1-score support
0 0.18 0.79 0.29 117971
1 0.91 0.39 0.55 692761
accuracy 0.45 810732
macro avg 0.55 0.59 0.42 810732
weighted avg 0.81 0.45 0.51 810732
Accuracy: 0.4465680397467967
90-100%
precision recall f1-score support
0 0.17 0.78 0.27 88944
1 0.92 0.40 0.56 577496
accuracy 0.45 666440
macro avg 0.54 0.59 0.41 666440
weighted avg 0.82 0.45 0.52 666440
Accuracy: 0.4483209291158994
Treshold: 0.7
All
precision recall f1-score support
0 0.58 1.00 0.73 22531902
1 0.87 0.03 0.07 16938696
accuracy 0.58 39470598
macro avg 0.72 0.52 0.40 39470598
weighted avg 0.70 0.58 0.45 39470598
Accuracy: 0.5835130747195673
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 0.53 0.01 0.01 1271288
accuracy 0.90 12711176
macro avg 0.72 0.50 0.48 12711176
weighted avg 0.86 0.90 0.85 12711176
Accuracy: 0.9000747059123404
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.75 0.02 0.04 3812372
accuracy 0.57 8856813
macro avg 0.66 0.51 0.38 8856813
weighted avg 0.65 0.57 0.43 8856813
Accuracy: 0.5748918939577927
20-40%
precision recall f1-score support
0 0.35 0.99 0.52 2995598
1 0.86 0.03 0.06 5583215
accuracy 0.37 8578813
macro avg 0.61 0.51 0.29 8578813
weighted avg 0.68 0.37 0.22 8578813
Accuracy: 0.3670397058427547
40-80%
precision recall f1-score support
0 0.21 0.98 0.35 1295061
1 0.92 0.05 0.09 5001564
accuracy 0.24 6296625
macro avg 0.56 0.52 0.22 6296625
weighted avg 0.77 0.24 0.15 6296625
Accuracy: 0.2413643817124253
80-90%
precision recall f1-score support
0 0.15 0.98 0.26 117971
1 0.94 0.06 0.11 692761
accuracy 0.19 810732
macro avg 0.55 0.52 0.19 810732
weighted avg 0.83 0.19 0.13 810732
Accuracy: 0.19361885308585328
90-100%
precision recall f1-score support
0 0.14 0.98 0.24 88944
1 0.94 0.06 0.12 577496
accuracy 0.19 666440
macro avg 0.54 0.52 0.18 666440
weighted avg 0.84 0.19 0.14 666440
Accuracy: 0.1851239421403277
Treshold: 0.8
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_7_w_0_75
0.01
Treshold: 0.6
All
precision recall f1-score support
0 0.68 0.90 0.77 28055468
1 0.78 0.44 0.56 21729815
accuracy 0.70 49785283
macro avg 0.73 0.67 0.67 49785283
weighted avg 0.72 0.70 0.68 49785283
Accuracy: 0.7010289566898715
0-1%
precision recall f1-score support
0 0.69 0.91 0.78 27764588
1 0.69 0.33 0.45 17098553
accuracy 0.69 44863141
macro avg 0.69 0.62 0.61 44863141
weighted avg 0.69 0.69 0.65 44863141
Accuracy: 0.6880236272355518
1-10%
precision recall f1-score support
0 0.08 0.19 0.11 287564
1 0.94 0.85 0.89 4164787
accuracy 0.81 4452351
macro avg 0.51 0.52 0.50 4452351
weighted avg 0.88 0.81 0.84 4452351
Accuracy: 0.8106463304442979
10-20%
precision recall f1-score support
0 0.01 0.07 0.02 2455
1 0.99 0.93 0.96 257616
accuracy 0.92 260071
macro avg 0.50 0.50 0.49 260071
weighted avg 0.98 0.92 0.95 260071
Accuracy: 0.9243629624218002
20-40%
precision recall f1-score support
0 0.01 0.12 0.01 659
1 1.00 0.90 0.95 130568
accuracy 0.90 131227
macro avg 0.50 0.51 0.48 131227
weighted avg 0.99 0.90 0.94 131227
Accuracy: 0.8987098691580239
40-80%
precision recall f1-score support
0 0.00 0.20 0.01 169
1 1.00 0.85 0.92 65234
accuracy 0.85 65403
macro avg 0.50 0.53 0.46 65403
weighted avg 1.00 0.85 0.92 65403
Accuracy: 0.8507255018882925
80-90%
precision recall f1-score support
0 0.00 0.20 0.00 15
1 1.00 0.82 0.90 7371
accuracy 0.82 7386
macro avg 0.50 0.51 0.45 7386
weighted avg 1.00 0.82 0.90 7386
Accuracy: 0.8216896831844029
90-100%
precision recall f1-score support
0 0.01 0.39 0.01 18
1 1.00 0.83 0.90 5686
accuracy 0.82 5704
macro avg 0.50 0.61 0.46 5704
weighted avg 0.99 0.82 0.90 5704
Accuracy: 0.823632538569425
Treshold: 0.7
All
precision recall f1-score support
0 0.60 0.98 0.75 28055468
1 0.89 0.17 0.28 21729815
accuracy 0.63 49785283
macro avg 0.75 0.58 0.51 49785283
weighted avg 0.73 0.63 0.54 49785283
Accuracy: 0.6273568235014352
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.77 0.06 0.11 17098553
accuracy 0.63 44863141
macro avg 0.70 0.52 0.44 44863141
weighted avg 0.69 0.63 0.52 44863141
Accuracy: 0.6343823095221978
1-10%
precision recall f1-score support
0 0.08 0.53 0.13 287564
1 0.94 0.55 0.69 4164787
accuracy 0.55 4452351
macro avg 0.51 0.54 0.41 4452351
weighted avg 0.89 0.55 0.66 4452351
Accuracy: 0.5476079940687515
10-20%
precision recall f1-score support
0 0.01 0.23 0.02 2455
1 0.99 0.78 0.87 257616
accuracy 0.78 260071
macro avg 0.50 0.50 0.45 260071
weighted avg 0.98 0.78 0.87 260071
Accuracy: 0.7768071026758078
20-40%
precision recall f1-score support
0 0.01 0.33 0.01 659
1 1.00 0.69 0.82 130568
accuracy 0.69 131227
macro avg 0.50 0.51 0.41 131227
weighted avg 0.99 0.69 0.81 131227
Accuracy: 0.6893246054546701
40-80%
precision recall f1-score support
0 0.00 0.48 0.01 169
1 1.00 0.55 0.71 65234
accuracy 0.55 65403
macro avg 0.50 0.52 0.36 65403
weighted avg 0.99 0.55 0.71 65403
Accuracy: 0.5524058529425255
80-90%
precision recall f1-score support
0 0.00 0.40 0.00 15
1 1.00 0.46 0.63 7371
accuracy 0.46 7386
macro avg 0.50 0.43 0.31 7386
weighted avg 1.00 0.46 0.63 7386
Accuracy: 0.45667479014351475
90-100%
precision recall f1-score support
0 0.00 0.50 0.01 18
1 1.00 0.46 0.63 5686
accuracy 0.46 5704
macro avg 0.50 0.48 0.32 5704
weighted avg 0.99 0.46 0.63 5704
Accuracy: 0.46037868162692847
Treshold: 0.8
All
precision recall f1-score support
0 0.58 1.00 0.73 28055468
1 0.95 0.05 0.10 21729815
accuracy 0.58 49785283
macro avg 0.76 0.52 0.41 49785283
weighted avg 0.74 0.58 0.45 49785283
Accuracy: 0.5848841915792665
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.74 0.00 0.01 17098553
accuracy 0.62 44863141
macro avg 0.68 0.50 0.39 44863141
weighted avg 0.67 0.62 0.48 44863141
Accuracy: 0.61957714908994
1-10%
precision recall f1-score support
0 0.07 0.85 0.13 287564
1 0.96 0.22 0.36 4164787
accuracy 0.26 4452351
macro avg 0.51 0.54 0.24 4452351
weighted avg 0.90 0.26 0.34 4452351
Accuracy: 0.2617493544421812
10-20%
precision recall f1-score support
0 0.01 0.52 0.02 2455
1 0.99 0.46 0.63 257616
accuracy 0.46 260071
macro avg 0.50 0.49 0.32 260071
weighted avg 0.98 0.46 0.63 260071
Accuracy: 0.4642693725944069
20-40%
precision recall f1-score support
0 0.00 0.71 0.01 659
1 0.99 0.25 0.40 130568
accuracy 0.25 131227
macro avg 0.50 0.48 0.20 131227
weighted avg 0.99 0.25 0.40 131227
Accuracy: 0.25135833326983015
40-80%
precision recall f1-score support
0 0.00 0.91 0.00 169
1 1.00 0.05 0.09 65234
accuracy 0.05 65403
macro avg 0.50 0.48 0.05 65403
weighted avg 0.99 0.05 0.09 65403
Accuracy: 0.04969191015702644
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 1.00 0.00 0.01 7371
accuracy 0.01 7386
macro avg 0.50 0.50 0.01 7386
weighted avg 1.00 0.01 0.01 7386
Accuracy: 0.005144868670457623
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 1.00 0.00 0.00 5686
accuracy 0.01 5704
macro avg 0.50 0.50 0.01 5704
weighted avg 1.00 0.01 0.00 5704
Accuracy: 0.005610098176718092
0.1
Treshold: 0.6
All
precision recall f1-score support
0 0.69 0.87 0.77 26119367
1 0.77 0.53 0.62 21615229
accuracy 0.71 47734596
macro avg 0.73 0.70 0.70 47734596
weighted avg 0.72 0.71 0.70 47734596
Accuracy: 0.712363691105713
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 0.53 12561431
weighted avg 0.93 0.95 0.94 12561431
Accuracy: 0.946364948388444
1-10%
precision recall f1-score support
0 0.55 0.79 0.65 13368467
1 0.68 0.41 0.51 14466820
accuracy 0.59 27835287
macro avg 0.62 0.60 0.58 27835287
weighted avg 0.62 0.59 0.58 27835287
Accuracy: 0.5943696215526716
10-20%
precision recall f1-score support
0 0.17 0.29 0.21 503365
1 0.88 0.79 0.83 3387274
accuracy 0.72 3890639
macro avg 0.53 0.54 0.52 3890639
weighted avg 0.79 0.72 0.75 3890639
Accuracy: 0.7230765948729759
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: 0.7897099644791831
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: 0.816456354355522
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: 0.8211406365893773
90-100%
precision recall f1-score support
0 0.03 0.23 0.06 2328
1 0.98 0.84 0.90 97067
accuracy 0.82 99395
macro avg 0.51 0.53 0.48 99395
weighted avg 0.96 0.82 0.88 99395
Accuracy: 0.8221037275516877
Treshold: 0.7
All
precision recall f1-score support
0 0.60 0.96 0.74 26119367
1 0.83 0.22 0.34 21615229
accuracy 0.63 47734596
macro avg 0.72 0.59 0.54 47734596
weighted avg 0.70 0.63 0.56 47734596
Accuracy: 0.625837767643409
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.23 0.01 0.03 508421
accuracy 0.96 12561431
macro avg 0.60 0.51 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9581693359618024
1-10%
precision recall f1-score support
0 0.50 0.95 0.65 13368467
1 0.71 0.11 0.19 14466820
accuracy 0.51 27835287
macro avg 0.61 0.53 0.42 27835287
weighted avg 0.61 0.51 0.41 27835287
Accuracy: 0.5148418983429199
10-20%
precision recall f1-score support
0 0.14 0.66 0.23 503365
1 0.89 0.39 0.54 3387274
accuracy 0.43 3890639
macro avg 0.51 0.53 0.39 3890639
weighted avg 0.79 0.43 0.50 3890639
Accuracy: 0.4256416490967165
20-40%
precision recall f1-score support
0 0.08 0.53 0.13 147488
1 0.94 0.52 0.67 1970425
accuracy 0.53 2117913
macro avg 0.51 0.53 0.40 2117913
weighted avg 0.88 0.53 0.64 2117913
Accuracy: 0.5250527287948088
40-80%
precision recall f1-score support
0 0.04 0.49 0.08 41616
1 0.97 0.56 0.71 1064279
accuracy 0.56 1105895
macro avg 0.50 0.53 0.39 1105895
weighted avg 0.93 0.56 0.68 1105895
Accuracy: 0.5566577297121336
80-90%
precision recall f1-score support
0 0.03 0.50 0.05 3093
1 0.98 0.56 0.71 120943
accuracy 0.55 124036
macro avg 0.50 0.53 0.38 124036
weighted avg 0.95 0.55 0.69 124036
Accuracy: 0.5545970524686381
90-100%
precision recall f1-score support
0 0.03 0.48 0.05 2328
1 0.98 0.55 0.71 97067
accuracy 0.55 99395
macro avg 0.50 0.52 0.38 99395
weighted avg 0.96 0.55 0.69 99395
Accuracy: 0.5526837366064692
Treshold: 0.8
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.71 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.63 0.50 0.35 47734596
weighted avg 0.62 0.55 0.39 47734596
Accuracy: 0.547201363137126
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: 0.9594811291802662
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.81 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.65 0.50 0.32 27835287
weighted avg 0.65 0.48 0.31 27835287
Accuracy: 0.4802708518866718
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.89 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.51 0.50 0.11 3890639
weighted avg 0.79 0.13 0.03 3890639
Accuracy: 0.12957408795830197
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.92 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.50 0.50 0.07 2117913
weighted avg 0.86 0.07 0.01 2117913
Accuracy: 0.07003498255121905
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 1.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.52 0.50 0.04 1105895
weighted avg 0.96 0.04 0.00 1105895
Accuracy: 0.037641909946242634
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: 0.6
All
precision recall f1-score support
0 0.69 0.87 0.77 24893266
1 0.77 0.53 0.63 20563095
accuracy 0.71 45456361
macro avg 0.73 0.70 0.70 45456361
weighted avg 0.72 0.71 0.70 45456361
Accuracy: 0.7141359819806077
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.02 0.03 0.02 3872
accuracy 1.00 4877461
macro avg 0.51 0.52 0.51 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9978650777525437
1-10%
precision recall f1-score support
0 0.72 0.90 0.80 16949103
1 0.56 0.28 0.37 8016772
accuracy 0.70 24965875
macro avg 0.64 0.59 0.59 24965875
weighted avg 0.67 0.70 0.66 24965875
Accuracy: 0.6974136896864219
10-20%
precision recall f1-score support
0 0.34 0.54 0.42 2057494
1 0.78 0.61 0.68 5461156
accuracy 0.59 7518650
macro avg 0.56 0.57 0.55 7518650
weighted avg 0.66 0.59 0.61 7518650
Accuracy: 0.5881461432571007
20-40%
precision recall f1-score support
0 0.22 0.39 0.28 744974
1 0.87 0.74 0.80 4060539
accuracy 0.69 4805513
macro avg 0.54 0.57 0.54 4805513
weighted avg 0.77 0.69 0.72 4805513
Accuracy: 0.6866779883854232
40-80%
precision recall f1-score support
0 0.13 0.34 0.19 235909
1 0.93 0.78 0.85 2483775
accuracy 0.74 2719684
macro avg 0.53 0.56 0.52 2719684
weighted avg 0.86 0.74 0.79 2719684
Accuracy: 0.7440886514756861
80-90%
precision recall f1-score support
0 0.09 0.32 0.14 18577
1 0.95 0.79 0.86 296772
accuracy 0.77 315349
macro avg 0.52 0.56 0.50 315349
weighted avg 0.90 0.77 0.82 315349
Accuracy: 0.7665887635603728
90-100%
precision recall f1-score support
0 0.08 0.32 0.13 13620
1 0.95 0.80 0.87 240209
accuracy 0.77 253829
macro avg 0.52 0.56 0.50 253829
weighted avg 0.91 0.77 0.83 253829
Accuracy: 0.7725594790193397
Treshold: 0.7
All
precision recall f1-score support
0 0.60 0.96 0.74 24893266
1 0.82 0.23 0.36 20563095
accuracy 0.63 45456361
macro avg 0.71 0.60 0.55 45456361
weighted avg 0.70 0.63 0.57 45456361
Accuracy: 0.6300721696573995
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.01 0.01 3872
accuracy 1.00 4877461
macro avg 0.52 0.50 0.51 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991124480544283
1-10%
precision recall f1-score support
0 0.69 0.97 0.81 16949103
1 0.61 0.09 0.15 8016772
accuracy 0.69 24965875
macro avg 0.65 0.53 0.48 24965875
weighted avg 0.67 0.69 0.60 24965875
Accuracy: 0.6885729020112453
10-20%
precision recall f1-score support
0 0.29 0.85 0.43 2057494
1 0.79 0.21 0.33 5461156
accuracy 0.39 7518650
macro avg 0.54 0.53 0.38 7518650
weighted avg 0.65 0.39 0.36 7518650
Accuracy: 0.3869113471168361
20-40%
precision recall f1-score support
0 0.17 0.72 0.28 744974
1 0.88 0.37 0.52 4060539
accuracy 0.42 4805513
macro avg 0.53 0.55 0.40 4805513
weighted avg 0.77 0.42 0.48 4805513
Accuracy: 0.42453532016248835
40-80%
precision recall f1-score support
0 0.10 0.62 0.17 235909
1 0.93 0.48 0.63 2483775
accuracy 0.49 2719684
macro avg 0.52 0.55 0.40 2719684
weighted avg 0.86 0.49 0.59 2719684
Accuracy: 0.4898171993511011
80-90%
precision recall f1-score support
0 0.07 0.59 0.13 18577
1 0.95 0.51 0.67 296772
accuracy 0.52 315349
macro avg 0.51 0.55 0.40 315349
weighted avg 0.90 0.52 0.63 315349
Accuracy: 0.5170874174327491
90-100%
precision recall f1-score support
0 0.06 0.58 0.12 13620
1 0.96 0.52 0.67 240209
accuracy 0.52 253829
macro avg 0.51 0.55 0.39 253829
weighted avg 0.91 0.52 0.64 253829
Accuracy: 0.5218434457843666
Treshold: 0.8
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: 0.6
All
precision recall f1-score support
0 0.70 0.89 0.78 22531902
1 0.77 0.49 0.60 16938696
accuracy 0.72 39470598
macro avg 0.73 0.69 0.69 39470598
weighted avg 0.73 0.72 0.70 39470598
Accuracy: 0.7184106002143672
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 0.39 0.14 0.21 1271288
accuracy 0.89 12711176
macro avg 0.65 0.56 0.58 12711176
weighted avg 0.86 0.89 0.87 12711176
Accuracy: 0.8918240137655241
10-20%
precision recall f1-score support
0 0.63 0.85 0.72 5044441
1 0.63 0.32 0.42 3812372
accuracy 0.63 8856813
macro avg 0.63 0.59 0.57 8856813
weighted avg 0.63 0.63 0.59 8856813
Accuracy: 0.6253006583745191
20-40%
precision recall f1-score support
0 0.45 0.70 0.55 2995598
1 0.77 0.53 0.63 5583215
accuracy 0.59 8578813
macro avg 0.61 0.62 0.59 8578813
weighted avg 0.66 0.59 0.60 8578813
Accuracy: 0.5924746232375039
40-80%
precision recall f1-score support
0 0.29 0.60 0.39 1295061
1 0.86 0.63 0.72 5001564
accuracy 0.62 6296625
macro avg 0.57 0.61 0.56 6296625
weighted avg 0.74 0.62 0.66 6296625
Accuracy: 0.6200054791257221
80-90%
precision recall f1-score support
0 0.22 0.57 0.31 117971
1 0.90 0.65 0.75 692761
accuracy 0.64 810732
macro avg 0.56 0.61 0.53 810732
weighted avg 0.80 0.64 0.69 810732
Accuracy: 0.6367763946655615
90-100%
precision recall f1-score support
0 0.20 0.56 0.30 88944
1 0.91 0.66 0.76 577496
accuracy 0.64 666440
macro avg 0.55 0.61 0.53 666440
weighted avg 0.81 0.64 0.70 666440
Accuracy: 0.6435207970710042
Treshold: 0.7
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 0.59 0.56 39470598
weighted avg 0.71 0.65 0.58 39470598
Accuracy: 0.6471920947334013
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 0.05 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: 0.8993622619968443
10-20%
precision recall f1-score support
0 0.59 0.96 0.73 5044441
1 0.68 0.13 0.21 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.47 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5986118257210579
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.82 0.23 0.35 5583215
accuracy 0.46 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.67 0.46 0.42 8578813
Accuracy: 0.46333006675865296
40-80%
precision recall f1-score support
0 0.24 0.85 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.42 6296625
macro avg 0.57 0.58 0.42 6296625
weighted avg 0.75 0.42 0.45 6296625
Accuracy: 0.424655748119032
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.41 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.41 0.47 810732
Accuracy: 0.41438601165366606
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.35 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: 0.4150996338755177
Treshold: 0.8
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.91 0.00 0.01 16938696
accuracy 0.57 39470598
macro avg 0.74 0.50 0.37 39470598
weighted avg 0.72 0.57 0.42 39470598
Accuracy: 0.5721525931783451
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 0.55 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.73 0.50 0.47 12711176
weighted avg 0.87 0.90 0.85 12711176
Accuracy: 0.8999977657456714
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.80 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.68 0.50 0.36 8856813
weighted avg 0.67 0.57 0.42 8856813
Accuracy: 0.5702003643974418
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.91 0.00 0.01 5583215
accuracy 0.35 8578813
macro avg 0.63 0.50 0.26 8578813
weighted avg 0.72 0.35 0.19 8578813
Accuracy: 0.35125034197621513
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.96 0.00 0.01 5001564
accuracy 0.21 6296625
macro avg 0.58 0.50 0.18 6296625
weighted avg 0.80 0.21 0.08 6296625
Accuracy: 0.20910853036348837
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.97 0.00 0.01 692761
accuracy 0.15 810732
macro avg 0.56 0.50 0.13 810732
weighted avg 0.85 0.15 0.05 810732
Accuracy: 0.1496191096441241
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.98 0.00 0.01 577496
accuracy 0.14 666440
macro avg 0.56 0.50 0.12 666440
weighted avg 0.86 0.14 0.04 666440
Accuracy: 0.13763879719104496
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_7[cache_size=0.01,treshold=0.8] | 9723106 | 0.404903 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 10130629 | 0.404909 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 9665622 | 0.404927 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 10205064 | 0.404963 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 10308093 | 0.405046 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 9504407 | 0.405077 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| Offline Clock 1st iteration | 10440959 | 0.405173 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 7836788 | 0.40828 | ../../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 |
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_7[cache_size=0.1,treshold=0.8] | 9741455 | 0.213588 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 9372212 | 0.213672 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 9125045 | 0.213803 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 10266558 | 0.213809 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| Offline Clock 1st iteration | 10273545 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 10273447 | 0.213818 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 10273392 | 0.213818 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 7247795 | 0.216211 | ../../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_7[cache_size=0.1,treshold=0.6] | 5360087 | 0.220696 | ../../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_w_0_5[cache_size=0.2,treshold=0.6] | 8954715 | 0.152718 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 9196565 | 0.152728 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 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_7[cache_size=0.2,treshold=0.8] | 9531967 | 0.152768 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 7120262 | 0.15423 | ../../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_7[cache_size=0.2,treshold=0.6] | 5229392 | 0.157674 | ../../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_w_0_5[cache_size=0.4,treshold=0.8] | 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_7_w_0_75[cache_size=0.4,treshold=0.8] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 9234302 | 0.0897435 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 8678767 | 0.0898427 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 8537633 | 0.0898543 | ../../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_7_w_0_75[cache_size=0.4,treshold=0.6] | 7072413 | 0.090343 | ../../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_7[cache_size=0.4,treshold=0.6] | 4886072 | 0.0923637 | ../../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_7[cache_size=0.01,treshold=0.8] | 9719385 | 0.405075 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 10126145 | 0.405082 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 9661889 | 0.405102 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 10201390 | 0.405133 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 10304584 | 0.405217 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 9499625 | 0.40526 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| Offline Clock 1st iteration | 10437637 | 0.405347 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 7834799 | 0.408448 | ../../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 |
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_7[cache_size=0.1,treshold=0.8] | 9743143 | 0.213754 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 9371039 | 0.213855 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 10267720 | 0.213974 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| Offline Clock 1st iteration | 10274590 | 0.213983 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 10274493 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 10274439 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 9125193 | 0.213987 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 7248211 | 0.216368 | ../../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_7[cache_size=0.1,treshold=0.6] | 5360305 | 0.22086 | ../../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_w_0_5[cache_size=0.2,treshold=0.6] | 8966724 | 0.152807 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 9207106 | 0.152818 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 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_7[cache_size=0.2,treshold=0.8] | 9547859 | 0.152851 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 7127190 | 0.154333 | ../../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_7[cache_size=0.2,treshold=0.6] | 5236734 | 0.157779 | ../../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_w_0_5[cache_size=0.4,treshold=0.8] | 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_7_w_0_75[cache_size=0.4,treshold=0.8] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 9242694 | 0.0897461 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 8686427 | 0.0898647 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 8544796 | 0.0898812 | ../../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_7_w_0_75[cache_size=0.4,treshold=0.6] | 7083588 | 0.0903566 | ../../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_7[cache_size=0.4,treshold=0.6] | 4894672 | 0.0923775 | ../../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_7[cache_size=0.01,treshold=0.8] | 9721381 | 0.404961 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 10128918 | 0.404974 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 9664049 | 0.404988 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 10203909 | 0.405024 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 10306504 | 0.405107 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 9500821 | 0.405148 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| Offline Clock 1st iteration | 10439561 | 0.405242 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 7836914 | 0.408333 | ../../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 |
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_7[cache_size=0.1,treshold=0.8] | 9739230 | 0.21363 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 9369942 | 0.213726 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 10265777 | 0.213843 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| Offline Clock 1st iteration | 10272630 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 10272536 | 0.213853 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 10272459 | 0.213853 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 9121962 | 0.213858 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 7245609 | 0.216245 | ../../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_7[cache_size=0.1,treshold=0.6] | 5357644 | 0.220741 | ../../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_w_0_5[cache_size=0.2,treshold=0.6] | 8960128 | 0.152738 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 9201293 | 0.152749 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 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_7[cache_size=0.2,treshold=0.8] | 9536570 | 0.152804 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 7122856 | 0.15426 | ../../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_7[cache_size=0.2,treshold=0.6] | 5231447 | 0.157695 | ../../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_w_0_5[cache_size=0.4,treshold=0.8] | 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_7_w_0_75[cache_size=0.4,treshold=0.8] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 9240479 | 0.0897082 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 8683798 | 0.0898224 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 8542602 | 0.0898437 | ../../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_7_w_0_75[cache_size=0.4,treshold=0.6] | 7076669 | 0.0903462 | ../../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_7[cache_size=0.4,treshold=0.6] | 4889127 | 0.0923508 | ../../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_7[cache_size=0.01,treshold=0.8] | 9722629 | 0.404917 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 10129870 | 0.404925 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 9665321 | 0.404946 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 10204455 | 0.404981 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 10307228 | 0.405066 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 9503273 | 0.405102 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| Offline Clock 1st iteration | 10439737 | 0.4052 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 7837368 | 0.408283 | ../../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 |
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_7[cache_size=0.1,treshold=0.8] | 9733356 | 0.213597 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 9365652 | 0.213688 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 10261679 | 0.21381 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 9117910 | 0.213816 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| Offline Clock 1st iteration | 10268394 | 0.213821 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 10268299 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 10268220 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 7246270 | 0.216207 | ../../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_7[cache_size=0.1,treshold=0.6] | 5361294 | 0.220688 | ../../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_w_0_5[cache_size=0.2,treshold=0.6] | 8958412 | 0.152669 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 9198976 | 0.152684 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 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_7[cache_size=0.2,treshold=0.8] | 9531160 | 0.152725 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 7124256 | 0.154171 | ../../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_7[cache_size=0.2,treshold=0.6] | 5230219 | 0.157625 | ../../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_w_0_5[cache_size=0.4,treshold=0.7] | 9239193 | 0.0896547 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.8] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.8] | 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_7_w_0_75[cache_size=0.4,treshold=0.7] | 8679101 | 0.0897776 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 8541240 | 0.0897861 | ../../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_7_w_0_75[cache_size=0.4,treshold=0.6] | 7071600 | 0.0902846 | ../../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_7[cache_size=0.4,treshold=0.6] | 4884998 | 0.0922988 | ../../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_7[cache_size=0.01,treshold=0.8] | 9724440 | 0.404975 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.7] | 10133038 | 0.404988 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.7] | 9666736 | 0.405001 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.8] | 10207388 | 0.405041 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.8] | 10310249 | 0.405126 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7_w_0_5[cache_size=0.01,treshold=0.6] | 9504429 | 0.40516 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| Offline Clock 1st iteration | 10442800 | 0.405256 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7_w_0_75[cache_size=0.01,treshold=0.6] | 7838599 | 0.408341 | ../../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 |
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_7[cache_size=0.1,treshold=0.8] | 9737676 | 0.213668 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.7] | 9368249 | 0.21376 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.7] | 10263795 | 0.213873 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| Offline Clock 1st iteration | 10270642 | 0.213882 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.8] | 10270549 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.8] | 10270498 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7_w_0_5[cache_size=0.1,treshold=0.6] | 9121423 | 0.213888 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7_w_0_75[cache_size=0.1,treshold=0.6] | 7245985 | 0.216268 | ../../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_7[cache_size=0.1,treshold=0.6] | 5359165 | 0.220761 | ../../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_w_0_5[cache_size=0.2,treshold=0.6] | 8963623 | 0.152749 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.7] | 9204046 | 0.152762 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.8] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.8] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7_w_0_5[cache_size=0.2,treshold=0.7] | 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_7[cache_size=0.2,treshold=0.8] | 9540045 | 0.15281 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7_w_0_75[cache_size=0.2,treshold=0.6] | 7122669 | 0.154279 | ../../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_7[cache_size=0.2,treshold=0.6] | 5231219 | 0.157735 | ../../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_w_0_5[cache_size=0.4,treshold=0.8] | 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_7_w_0_75[cache_size=0.4,treshold=0.8] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.7] | 9241413 | 0.089703 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7_w_0_75[cache_size=0.4,treshold=0.7] | 8687945 | 0.0898086 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7_w_0_5[cache_size=0.4,treshold=0.6] | 8546144 | 0.0898246 | ../../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_7_w_0_75[cache_size=0.4,treshold=0.6] | 7078806 | 0.0903325 | ../../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 |