Zipf1 New Model With Selected Treshold Test Data Result Obj Size Ignored
Result
Model Summaries
| Model | Better than base % of the times |
|---|
| LR_7[cache_size=0.01,treshold=0.8] | 100 |
| LR_7[cache_size=0.01,treshold=0.9] | 100 |
| LR_8[cache_size=0.01,treshold=0.8] | 100 |
| LR_8[cache_size=0.01,treshold=0.9] | 100 |
| LR_9[cache_size=0.01,treshold=0.8] | 100 |
| LR_9[cache_size=0.01,treshold=0.9] | 100 |
| LR_7[cache_size=0.1,treshold=0.8] | 100 |
| LR_7[cache_size=0.1,treshold=0.9] | 0 |
| LR_8[cache_size=0.1,treshold=0.8] | 100 |
| LR_8[cache_size=0.1,treshold=0.9] | 0 |
| LR_9[cache_size=0.1,treshold=0.8] | 100 |
| LR_9[cache_size=0.1,treshold=0.9] | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 |
| LR_8[cache_size=0.2,treshold=0.8] | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 |
| LR_9[cache_size=0.2,treshold=0.8] | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 |
| LR_7[cache_size=0.4,treshold=0.8] | 0 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 |
| LR_8[cache_size=0.4,treshold=0.8] | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 |
| Offline Clock 1st iteration | 0 |
| Offline Clock 2nd iteration | 100 |
| Zipf Optimal Distribution | 100 |
| Model | Max | Min | Avg | Mdn |
|---|
| LR_7[cache_size=0.01,treshold=0.8] | 6.88137 | 6.86902 | 6.87683 | 6.879 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34773 | 1.34061 | 1.34513 | 1.34701 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.72185 | 6.70669 | 6.71479 | 6.71621 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.36124 | 1.35674 | 1.35946 | 1.35994 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.40022 | 6.38711 | 6.39412 | 6.39562 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.35214 | 1.34658 | 1.34921 | 1.34993 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.21053 | 5.17244 | 5.18877 | 5.18922 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000555101 | 0.000506297 | 0.000531545 | 0.000525669 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.23996 | 5.20562 | 5.2224 | 5.22281 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.00056484 | 0.000535507 | 0.000551015 | 0.000545138 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.12955 | 5.09796 | 5.10997 | 5.11123 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000545034 | 0.000516034 | 0.000529597 | 0.000525669 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.69871 | 4.62173 | 4.65984 | 4.66176 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.83334 | 4.74239 | 4.79185 | 4.79728 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.70314 | 4.62542 | 4.6636 | 4.66471 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.85173 | 6.80302 | 6.83317 | 6.84329 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.8552 | 6.80659 | 6.83671 | 6.84693 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.845 | 6.79686 | 6.82601 | 6.83324 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 | 0 | 0 |
| Offline Clock 2nd iteration | 43.4673 | 41.4753 | 42.6567 | 43.0175 |
| Zipf Optimal Distribution | 17.0869 | 6.59027 | 12.1282 | 13.1121 |
Miss Ratio Reduced (%)
| Model | Max | Min | Avg | Mdn |
|---|
| LR_7[cache_size=0.01,treshold=0.8] | 0.0698421 | 0.0666382 | 0.0684527 | 0.0693389 |
| LR_7[cache_size=0.01,treshold=0.9] | 0.0352876 | 0.0328255 | 0.0341523 | 0.0340449 |
| LR_8[cache_size=0.01,treshold=0.8] | 0.0767522 | 0.0742574 | 0.0754115 | 0.0752611 |
| LR_8[cache_size=0.01,treshold=0.9] | 0.0357811 | 0.0335659 | 0.0346951 | 0.034785 |
| LR_9[cache_size=0.01,treshold=0.8] | 0.0846408 | 0.0816584 | 0.0833573 | 0.0836508 |
| LR_9[cache_size=0.01,treshold=0.9] | 0.0357811 | 0.0335659 | 0.0346458 | 0.0345383 |
| LR_7[cache_size=0.1,treshold=0.8] | 0.107101 | 0.100055 | 0.104549 | 0.104761 |
| LR_7[cache_size=0.1,treshold=0.9] | 0 | -0.000467681 | -0.000280511 | -0.000467327 |
| LR_8[cache_size=0.1,treshold=0.8] | 0.106633 | 0.100055 | 0.104268 | 0.104761 |
| LR_8[cache_size=0.1,treshold=0.9] | 0 | -0.000467681 | -0.000280511 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.8] | 0.10842 | 0.101458 | 0.105765 | 0.106164 |
| LR_9[cache_size=0.1,treshold=0.9] | 0 | -0.000467681 | -0.000280511 | -0.000467327 |
| LR_7[cache_size=0.2,treshold=0.8] | -0.00981444 | -0.0124422 | -0.0117823 | -0.0124353 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.8] | -0.011123 | -0.0130933 | -0.012175 | -0.0124358 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.8] | -0.0104687 | -0.0130971 | -0.0124369 | -0.0130898 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.8] | -0.134606 | -0.159964 | -0.150485 | -0.157828 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.8] | -0.134829 | -0.159852 | -0.150596 | -0.158051 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | -0.13416 | -0.159964 | -0.150239 | -0.157605 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 | 0 | 0 |
| Offline Clock 2nd iteration | 7.80369 | 0.100977 | 2.73498 | 1.84941 |
| Zipf Optimal Distribution | 3.35401 | 0.0684004 | 1.23463 | 0.902408 |
Model Summaries Plot
Miss Ratio Reduced (%)
Cache Size All
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 42.6567 | 2.73498 |
| Zipf Optimal Distribution | 12.1282 | 1.23463 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.10997 | 0.105765 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18877 | 0.104549 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.2224 | 0.104268 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39412 | 0.0833573 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71479 | 0.0754115 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.87683 | 0.0684527 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35946 | 0.0346951 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34921 | 0.0346458 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34513 | 0.0341523 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000531545 | -0.000280511 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000551015 | -0.000280511 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000529597 | -0.000280511 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.65984 | -0.0117823 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79185 | -0.012175 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.6636 | -0.0124369 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.82601 | -0.150239 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.83317 | -0.150485 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.83671 | -0.150596 |
Cache Size 0.01
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 42.0861 | 0.362449 |
| Zipf Optimal Distribution | 8.83002 | 0.192773 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39412 | 0.0833573 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71479 | 0.0754115 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.87683 | 0.0684527 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35946 | 0.0346951 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34921 | 0.0346458 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34513 | 0.0341523 |
| Offline Clock 1st iteration | 0 | 0 |
Cache Size 0.1
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.0216 | 1.84971 |
| Zipf Optimal Distribution | 13.1079 | 0.901478 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.10997 | 0.105765 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18877 | 0.104549 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.2224 | 0.104268 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000531545 | -0.000280511 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000551015 | -0.000280511 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000529597 | -0.000280511 |
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 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.65984 | -0.0117823 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79185 | -0.012175 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.6636 | -0.0124369 |
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[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.82601 | -0.150239 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.83317 | -0.150485 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.83671 | -0.150596 |
Cache Size All
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.0175 | 1.84941 |
| Zipf Optimal Distribution | 13.1121 | 0.902408 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.11123 | 0.106164 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.22281 | 0.104761 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18922 | 0.104761 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39562 | 0.0836508 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71621 | 0.0752611 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.879 | 0.0693389 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35994 | 0.034785 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34993 | 0.0345383 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34701 | 0.0340449 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000545138 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.66176 | -0.0124353 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79728 | -0.0124358 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.66471 | -0.0130898 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.83324 | -0.157605 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.84329 | -0.157828 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.84693 | -0.158051 |
Cache Size 0.01
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 42.0861 | 0.361512 |
| Zipf Optimal Distribution | 8.82408 | 0.192718 |
| LR_9[cache_size=0.01,treshold=0.8] | 6.39562 | 0.0836508 |
| LR_8[cache_size=0.01,treshold=0.8] | 6.71621 | 0.0752611 |
| LR_7[cache_size=0.01,treshold=0.8] | 6.879 | 0.0693389 |
| LR_8[cache_size=0.01,treshold=0.9] | 1.35994 | 0.034785 |
| LR_9[cache_size=0.01,treshold=0.9] | 1.34993 | 0.0345383 |
| LR_7[cache_size=0.01,treshold=0.9] | 1.34701 | 0.0340449 |
| Offline Clock 1st iteration | 0 | 0 |
Cache Size 0.1
| Model | Promotion Reduced (%) | Miss Ratio Reduced (%) |
|---|
| Offline Clock 2nd iteration | 43.0175 | 1.84941 |
| Zipf Optimal Distribution | 13.1121 | 0.902408 |
| LR_9[cache_size=0.1,treshold=0.8] | 5.11123 | 0.106164 |
| LR_7[cache_size=0.1,treshold=0.8] | 5.18922 | 0.104761 |
| LR_8[cache_size=0.1,treshold=0.8] | 5.22281 | 0.104761 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
| LR_8[cache_size=0.1,treshold=0.9] | 0.000545138 | -0.000467327 |
| LR_9[cache_size=0.1,treshold=0.9] | 0.000525669 | -0.000467327 |
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 |
| Offline Clock 1st iteration | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.2,treshold=0.9] | 0 | 0 |
| LR_7[cache_size=0.2,treshold=0.8] | 4.66176 | -0.0124353 |
| LR_8[cache_size=0.2,treshold=0.8] | 4.79728 | -0.0124358 |
| LR_9[cache_size=0.2,treshold=0.8] | 4.66471 | -0.0130898 |
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[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_8[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.9] | 0 | 0 |
| LR_9[cache_size=0.4,treshold=0.8] | 6.83324 | -0.157605 |
| LR_7[cache_size=0.4,treshold=0.8] | 6.84329 | -0.157828 |
| LR_8[cache_size=0.4,treshold=0.8] | 6.84693 | -0.158051 |
Model Classification Report
LR_7
0.01
Treshold: 0.8
All
precision recall f1-score support
0 0.60 0.99 0.75 28055468
1 0.90 0.16 0.27 21729815
accuracy 0.62 49785283
macro avg 0.75 0.57 0.51 49785283
weighted avg 0.73 0.62 0.54 49785283
Accuracy: 0.623849602301146
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.78 0.05 0.10 17098553
accuracy 0.63 44863141
macro avg 0.70 0.52 0.43 44863141
weighted avg 0.69 0.63 0.51 44863141
Accuracy: 0.6327755785088699
1-10%
precision recall f1-score support
0 0.07 0.56 0.13 287564
1 0.94 0.52 0.67 4164787
accuracy 0.53 4452351
macro avg 0.51 0.54 0.40 4452351
weighted avg 0.89 0.53 0.64 4452351
Accuracy: 0.5269303790289669
10-20%
precision recall f1-score support
0 0.01 0.24 0.02 2455
1 0.99 0.76 0.86 257616
accuracy 0.76 260071
macro avg 0.50 0.50 0.44 260071
weighted avg 0.98 0.76 0.85 260071
Accuracy: 0.7580468410549427
20-40%
precision recall f1-score support
0 0.01 0.36 0.01 659
1 1.00 0.67 0.80 130568
accuracy 0.66 131227
macro avg 0.50 0.51 0.40 131227
weighted avg 0.99 0.66 0.79 131227
Accuracy: 0.6645354995542075
40-80%
precision recall f1-score support
0 0.00 0.51 0.01 169
1 1.00 0.52 0.69 65234
accuracy 0.52 65403
macro avg 0.50 0.52 0.35 65403
weighted avg 0.99 0.52 0.68 65403
Accuracy: 0.5224072290261914
80-90%
precision recall f1-score support
0 0.00 0.47 0.00 15
1 1.00 0.43 0.60 7371
accuracy 0.43 7386
macro avg 0.50 0.45 0.30 7386
weighted avg 1.00 0.43 0.60 7386
Accuracy: 0.4309504467912266
90-100%
precision recall f1-score support
0 0.00 0.56 0.01 18
1 1.00 0.43 0.60 5686
accuracy 0.43 5704
macro avg 0.50 0.49 0.30 5704
weighted avg 0.99 0.43 0.60 5704
Accuracy: 0.42934782608695654
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 28055468
1 0.95 0.03 0.06 21729815
accuracy 0.58 49785283
macro avg 0.76 0.51 0.39 49785283
weighted avg 0.74 0.58 0.44 49785283
Accuracy: 0.5762185784903543
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.55 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.58 0.50 0.38 44863141
weighted avg 0.59 0.62 0.47 44863141
Accuracy: 0.6189122602895771
1-10%
precision recall f1-score support
0 0.07 0.92 0.13 287564
1 0.96 0.14 0.24 4164787
accuracy 0.19 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.19 0.23 4452351
Accuracy: 0.18617085670020175
10-20%
precision recall f1-score support
0 0.01 0.69 0.02 2455
1 0.99 0.30 0.46 257616
accuracy 0.31 260071
macro avg 0.50 0.50 0.24 260071
weighted avg 0.98 0.31 0.46 260071
Accuracy: 0.30700078055607893
20-40%
precision recall f1-score support
0 0.00 0.90 0.01 659
1 0.99 0.09 0.16 130568
accuracy 0.09 131227
macro avg 0.50 0.49 0.08 131227
weighted avg 0.99 0.09 0.16 131227
Accuracy: 0.08976811174529632
40-80%
precision recall f1-score support
0 0.00 1.00 0.01 169
1 1.00 0.00 0.00 65234
accuracy 0.00 65403
macro avg 0.50 0.50 0.00 65403
weighted avg 1.00 0.00 0.00 65403
Accuracy: 0.004648104826995704
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 0.00 0.00 0.00 7371
accuracy 0.00 7386
macro avg 0.00 0.50 0.00 7386
weighted avg 0.00 0.00 0.00 7386
Accuracy: 0.0020308692120227455
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 0.00 0.00 0.00 5686
accuracy 0.00 5704
macro avg 0.00 0.50 0.00 5704
weighted avg 0.00 0.00 0.00 5704
Accuracy: 0.003155680224403927
0.1
Treshold: 0.8
All
precision recall f1-score support
0 0.58 0.98 0.73 26119367
1 0.85 0.15 0.26 21615229
accuracy 0.60 47734596
macro avg 0.72 0.56 0.49 47734596
weighted avg 0.70 0.60 0.52 47734596
Accuracy: 0.6038039161366318
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.25 0.01 0.02 508421
accuracy 0.96 12561431
macro avg 0.60 0.50 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9588727590033334
1-10%
precision recall f1-score support
0 0.49 0.97 0.65 13368467
1 0.72 0.07 0.12 14466820
accuracy 0.50 27835287
macro avg 0.60 0.52 0.39 27835287
weighted avg 0.61 0.50 0.38 27835287
Accuracy: 0.501558687000425
10-20%
precision recall f1-score support
0 0.14 0.77 0.23 503365
1 0.89 0.27 0.41 3387274
accuracy 0.33 3890639
macro avg 0.51 0.52 0.32 3890639
weighted avg 0.79 0.33 0.39 3890639
Accuracy: 0.33381920039356006
20-40%
precision recall f1-score support
0 0.07 0.63 0.13 147488
1 0.94 0.41 0.57 1970425
accuracy 0.43 2117913
macro avg 0.51 0.52 0.35 2117913
weighted avg 0.88 0.43 0.54 2117913
Accuracy: 0.4275987729429868
40-80%
precision recall f1-score support
0 0.04 0.59 0.08 41616
1 0.97 0.46 0.62 1064279
accuracy 0.46 1105895
macro avg 0.50 0.52 0.35 1105895
weighted avg 0.93 0.46 0.60 1105895
Accuracy: 0.4609424945406209
80-90%
precision recall f1-score support
0 0.03 0.60 0.05 3093
1 0.98 0.46 0.62 120943
accuracy 0.46 124036
macro avg 0.50 0.53 0.34 124036
weighted avg 0.95 0.46 0.61 124036
Accuracy: 0.45997936083072655
90-100%
precision recall f1-score support
0 0.02 0.57 0.05 2328
1 0.98 0.45 0.62 97067
accuracy 0.46 99395
macro avg 0.50 0.51 0.33 99395
weighted avg 0.96 0.46 0.61 99395
Accuracy: 0.4557271492529805
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.00 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.27 0.50 0.35 47734596
weighted avg 0.30 0.55 0.39 47734596
Accuracy: 0.5471723275923399
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.00 0.00 0.00 508421
accuracy 0.96 12561431
macro avg 0.48 0.50 0.49 12561431
weighted avg 0.92 0.96 0.94 12561431
Accuracy: 0.95949999645741
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.00 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.24 0.50 0.32 27835287
weighted avg 0.23 0.48 0.31 27835287
Accuracy: 0.4802704926304514
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.00 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.06 0.50 0.11 3890639
weighted avg 0.02 0.13 0.03 3890639
Accuracy: 0.12937849026856513
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.00 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.03 0.50 0.07 2117913
weighted avg 0.00 0.07 0.01 2117913
Accuracy: 0.0696383656930195
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 0.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.02 0.50 0.04 1105895
weighted avg 0.00 0.04 0.00 1105895
Accuracy: 0.03763105900650604
80-90%
precision recall f1-score support
0 0.02 1.00 0.05 3093
1 0.00 0.00 0.00 120943
accuracy 0.02 124036
macro avg 0.01 0.50 0.02 124036
weighted avg 0.00 0.02 0.00 124036
Accuracy: 0.024936308813570254
90-100%
precision recall f1-score support
0 0.02 1.00 0.05 2328
1 0.00 0.00 0.00 97067
accuracy 0.02 99395
macro avg 0.01 0.50 0.02 99395
weighted avg 0.00 0.02 0.00 99395
Accuracy: 0.023421701292821572
0.2
Treshold: 0.8
All
precision recall f1-score support
0 0.59 0.97 0.73 24893266
1 0.83 0.17 0.28 20563095
accuracy 0.61 45456361
macro avg 0.71 0.57 0.51 45456361
weighted avg 0.69 0.61 0.53 45456361
Accuracy: 0.6077220083675418
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.00 0.01 3872
accuracy 1.00 4877461
macro avg 0.52 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991612439340878
1-10%
precision recall f1-score support
0 0.69 0.98 0.81 16949103
1 0.62 0.06 0.11 8016772
accuracy 0.69 24965875
macro avg 0.65 0.52 0.46 24965875
weighted avg 0.67 0.69 0.59 24965875
Accuracy: 0.6862760468038873
10-20%
precision recall f1-score support
0 0.28 0.90 0.43 2057494
1 0.79 0.15 0.25 5461156
accuracy 0.35 7518650
macro avg 0.54 0.52 0.34 7518650
weighted avg 0.66 0.35 0.30 7518650
Accuracy: 0.3530327917910795
20-40%
precision recall f1-score support
0 0.17 0.81 0.28 744974
1 0.88 0.26 0.40 4060539
accuracy 0.34 4805513
macro avg 0.52 0.53 0.34 4805513
weighted avg 0.77 0.34 0.38 4805513
Accuracy: 0.3438069983371182
40-80%
precision recall f1-score support
0 0.10 0.72 0.17 235909
1 0.93 0.36 0.52 2483775
accuracy 0.39 2719684
macro avg 0.51 0.54 0.35 2719684
weighted avg 0.86 0.39 0.49 2719684
Accuracy: 0.39309125619005736
80-90%
precision recall f1-score support
0 0.07 0.68 0.12 18577
1 0.95 0.41 0.57 296772
accuracy 0.42 315349
macro avg 0.51 0.54 0.35 315349
weighted avg 0.90 0.42 0.54 315349
Accuracy: 0.42294410319994674
90-100%
precision recall f1-score support
0 0.06 0.67 0.11 13620
1 0.96 0.42 0.58 240209
accuracy 0.43 253829
macro avg 0.51 0.54 0.35 253829
weighted avg 0.91 0.43 0.55 253829
Accuracy: 0.4295056908391082
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.00 0.00 0.00 20563095
accuracy 0.55 45456361
macro avg 0.27 0.50 0.35 45456361
weighted avg 0.30 0.55 0.39 45456361
Accuracy: 0.5476299785633962
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.00 0.00 0.00 3872
accuracy 1.00 4877461
macro avg 0.50 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9992061443443627
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.00 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.34 0.50 0.40 24965875
weighted avg 0.46 0.68 0.55 24965875
Accuracy: 0.678890805950122
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.00 0.00 0.00 5461156
accuracy 0.27 7518650
macro avg 0.14 0.50 0.21 7518650
weighted avg 0.07 0.27 0.12 7518650
Accuracy: 0.2736520518976146
20-40%
precision recall f1-score support
0 0.16 1.00 0.27 744974
1 0.00 0.00 0.00 4060539
accuracy 0.16 4805513
macro avg 0.08 0.50 0.13 4805513
weighted avg 0.02 0.16 0.04 4805513
Accuracy: 0.15502486415082012
40-80%
precision recall f1-score support
0 0.09 1.00 0.16 235909
1 0.00 0.00 0.00 2483775
accuracy 0.09 2719684
macro avg 0.04 0.50 0.08 2719684
weighted avg 0.01 0.09 0.01 2719684
Accuracy: 0.08674132730126
80-90%
precision recall f1-score support
0 0.06 1.00 0.11 18577
1 0.00 0.00 0.00 296772
accuracy 0.06 315349
macro avg 0.03 0.50 0.06 315349
weighted avg 0.00 0.06 0.01 315349
Accuracy: 0.05890933537128705
90-100%
precision recall f1-score support
0 0.05 1.00 0.10 13620
1 0.00 0.00 0.00 240209
accuracy 0.05 253829
macro avg 0.03 0.50 0.05 253829
weighted avg 0.00 0.05 0.01 253829
Accuracy: 0.05365817144613105
0.4
Treshold: 0.8
All
precision recall f1-score support
0 0.62 0.96 0.76 22531902
1 0.82 0.23 0.36 16938696
accuracy 0.65 39470598
macro avg 0.72 0.60 0.56 39470598
weighted avg 0.71 0.65 0.59 39470598
Accuracy: 0.6486970377291978
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 0.99 0.95 11439888
1 0.47 0.06 0.10 1271288
accuracy 0.90 12711176
macro avg 0.69 0.52 0.52 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.8992394566796966
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.13 0.22 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.48 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5995312309292293
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.81 0.23 0.36 5583215
accuracy 0.47 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.66 0.47 0.43 8578813
Accuracy: 0.4669942100381486
40-80%
precision recall f1-score support
0 0.24 0.84 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.43 6296625
macro avg 0.56 0.58 0.42 6296625
weighted avg 0.75 0.43 0.45 6296625
Accuracy: 0.42776217418061263
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.42 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.42 0.47 810732
Accuracy: 0.41582668502045067
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.36 0.51 577496
accuracy 0.42 666440
macro avg 0.54 0.58 0.39 666440
weighted avg 0.82 0.42 0.48 666440
Accuracy: 0.41608546905948024
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.00 0.00 0.00 16938696
accuracy 0.57 39470598
macro avg 0.29 0.50 0.36 39470598
weighted avg 0.33 0.57 0.41 39470598
Accuracy: 0.5708528155565314
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 1.00 0.95 11439888
1 0.00 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.45 0.50 0.47 12711176
weighted avg 0.81 0.90 0.85 12711176
Accuracy: 0.8999865944740282
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.00 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.28 0.50 0.36 8856813
weighted avg 0.32 0.57 0.41 8856813
Accuracy: 0.5695548726161431
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.00 0.00 0.00 5583215
accuracy 0.35 8578813
macro avg 0.17 0.50 0.26 8578813
weighted avg 0.12 0.35 0.18 8578813
Accuracy: 0.34918560411562766
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.00 0.00 0.00 5001564
accuracy 0.21 6296625
macro avg 0.10 0.50 0.17 6296625
weighted avg 0.04 0.21 0.07 6296625
Accuracy: 0.20567542135667918
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.00 0.00 0.00 692761
accuracy 0.15 810732
macro avg 0.07 0.50 0.13 810732
weighted avg 0.02 0.15 0.04 810732
Accuracy: 0.14551171040491803
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.00 0.00 0.00 577496
accuracy 0.13 666440
macro avg 0.07 0.50 0.12 666440
weighted avg 0.02 0.13 0.03 666440
Accuracy: 0.13346137686813517
LR_8
0.01
Treshold: 0.8
All
precision recall f1-score support
0 0.60 0.99 0.75 28055468
1 0.90 0.15 0.26 21729815
accuracy 0.62 49785283
macro avg 0.75 0.57 0.50 49785283
weighted avg 0.73 0.62 0.53 49785283
Accuracy: 0.6226645532978089
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.78 0.05 0.09 17098553
accuracy 0.63 44863141
macro avg 0.71 0.52 0.43 44863141
weighted avg 0.69 0.63 0.51 44863141
Accuracy: 0.6318400443696085
1-10%
precision recall f1-score support
0 0.07 0.56 0.13 287564
1 0.94 0.52 0.67 4164787
accuracy 0.52 4452351
macro avg 0.51 0.54 0.40 4452351
weighted avg 0.89 0.52 0.64 4452351
Accuracy: 0.5229810048668669
10-20%
precision recall f1-score support
0 0.01 0.25 0.02 2455
1 0.99 0.76 0.86 257616
accuracy 0.76 260071
macro avg 0.50 0.51 0.44 260071
weighted avg 0.98 0.76 0.86 260071
Accuracy: 0.7600386048425237
20-40%
precision recall f1-score support
0 0.01 0.36 0.01 659
1 1.00 0.67 0.80 130568
accuracy 0.67 131227
macro avg 0.50 0.51 0.41 131227
weighted avg 0.99 0.67 0.80 131227
Accuracy: 0.6670807074763577
40-80%
precision recall f1-score support
0 0.00 0.50 0.01 169
1 1.00 0.52 0.68 65234
accuracy 0.52 65403
macro avg 0.50 0.51 0.34 65403
weighted avg 0.99 0.52 0.68 65403
Accuracy: 0.5198232496980261
80-90%
precision recall f1-score support
0 0.00 0.53 0.00 15
1 1.00 0.42 0.59 7371
accuracy 0.42 7386
macro avg 0.50 0.48 0.30 7386
weighted avg 1.00 0.42 0.59 7386
Accuracy: 0.4217438396967235
90-100%
precision recall f1-score support
0 0.00 0.56 0.01 18
1 1.00 0.42 0.59 5686
accuracy 0.42 5704
macro avg 0.50 0.49 0.30 5704
weighted avg 0.99 0.42 0.59 5704
Accuracy: 0.41917952314165496
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 28055468
1 0.95 0.03 0.06 21729815
accuracy 0.58 49785283
macro avg 0.76 0.51 0.39 49785283
weighted avg 0.74 0.58 0.44 49785283
Accuracy: 0.5763193713290733
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.56 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.59 0.50 0.38 44863141
weighted avg 0.60 0.62 0.47 44863141
Accuracy: 0.6189191256136078
1-10%
precision recall f1-score support
0 0.07 0.92 0.13 287564
1 0.96 0.14 0.24 4164787
accuracy 0.19 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.19 0.23 4452351
Accuracy: 0.18705465943722765
10-20%
precision recall f1-score support
0 0.01 0.69 0.02 2455
1 0.99 0.31 0.47 257616
accuracy 0.31 260071
macro avg 0.50 0.50 0.24 260071
weighted avg 0.98 0.31 0.46 260071
Accuracy: 0.3102037520523242
20-40%
precision recall f1-score support
0 0.00 0.90 0.01 659
1 0.99 0.09 0.16 130568
accuracy 0.09 131227
macro avg 0.50 0.49 0.08 131227
weighted avg 0.99 0.09 0.16 131227
Accuracy: 0.08940233336127473
40-80%
precision recall f1-score support
0 0.00 1.00 0.01 169
1 1.00 0.00 0.00 65234
accuracy 0.00 65403
macro avg 0.50 0.50 0.00 65403
weighted avg 1.00 0.00 0.00 65403
Accuracy: 0.00449520664189716
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 0.00 0.00 0.00 7371
accuracy 0.00 7386
macro avg 0.00 0.50 0.00 7386
weighted avg 0.00 0.00 0.00 7386
Accuracy: 0.0020308692120227455
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 0.00 0.00 0.00 5686
accuracy 0.00 5704
macro avg 0.00 0.50 0.00 5704
weighted avg 0.00 0.00 0.00 5704
Accuracy: 0.003155680224403927
0.1
Treshold: 0.8
All
precision recall f1-score support
0 0.58 0.98 0.73 26119367
1 0.85 0.15 0.26 21615229
accuracy 0.60 47734596
macro avg 0.72 0.57 0.49 47734596
weighted avg 0.70 0.60 0.52 47734596
Accuracy: 0.6040380021232399
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.25 0.01 0.02 508421
accuracy 0.96 12561431
macro avg 0.61 0.50 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9588680620862384
1-10%
precision recall f1-score support
0 0.49 0.97 0.65 13368467
1 0.72 0.07 0.12 14466820
accuracy 0.50 27835287
macro avg 0.60 0.52 0.39 27835287
weighted avg 0.61 0.50 0.38 27835287
Accuracy: 0.5017235856055661
10-20%
precision recall f1-score support
0 0.14 0.77 0.23 503365
1 0.89 0.27 0.41 3387274
accuracy 0.33 3890639
macro avg 0.51 0.52 0.32 3890639
weighted avg 0.79 0.33 0.39 3890639
Accuracy: 0.33489614430945663
20-40%
precision recall f1-score support
0 0.07 0.63 0.13 147488
1 0.94 0.41 0.57 1970425
accuracy 0.43 2117913
macro avg 0.51 0.52 0.35 2117913
weighted avg 0.88 0.43 0.54 2117913
Accuracy: 0.42843166834520585
40-80%
precision recall f1-score support
0 0.04 0.59 0.08 41616
1 0.97 0.46 0.62 1064279
accuracy 0.46 1105895
macro avg 0.50 0.52 0.35 1105895
weighted avg 0.93 0.46 0.60 1105895
Accuracy: 0.4614669566278896
80-90%
precision recall f1-score support
0 0.03 0.60 0.05 3093
1 0.98 0.46 0.62 120943
accuracy 0.46 124036
macro avg 0.50 0.53 0.34 124036
weighted avg 0.95 0.46 0.61 124036
Accuracy: 0.46047921571156764
90-100%
precision recall f1-score support
0 0.02 0.57 0.05 2328
1 0.98 0.45 0.62 97067
accuracy 0.46 99395
macro avg 0.50 0.51 0.33 99395
weighted avg 0.96 0.46 0.61 99395
Accuracy: 0.45620001006086824
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.00 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.27 0.50 0.35 47734596
weighted avg 0.30 0.55 0.39 47734596
Accuracy: 0.5471720762023418
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.00 0.00 0.00 508421
accuracy 0.96 12561431
macro avg 0.48 0.50 0.49 12561431
weighted avg 0.92 0.96 0.94 12561431
Accuracy: 0.9594990411522382
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.00 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.24 0.50 0.32 27835287
weighted avg 0.23 0.48 0.31 27835287
Accuracy: 0.4802704926304514
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.00 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.06 0.50 0.11 3890639
weighted avg 0.02 0.13 0.03 3890639
Accuracy: 0.12937849026856513
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.00 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.03 0.50 0.07 2117913
weighted avg 0.00 0.07 0.01 2117913
Accuracy: 0.0696383656930195
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 0.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.02 0.50 0.04 1105895
weighted avg 0.00 0.04 0.00 1105895
Accuracy: 0.03763105900650604
80-90%
precision recall f1-score support
0 0.02 1.00 0.05 3093
1 0.00 0.00 0.00 120943
accuracy 0.02 124036
macro avg 0.01 0.50 0.02 124036
weighted avg 0.00 0.02 0.00 124036
Accuracy: 0.024936308813570254
90-100%
precision recall f1-score support
0 0.02 1.00 0.05 2328
1 0.00 0.00 0.00 97067
accuracy 0.02 99395
macro avg 0.01 0.50 0.02 99395
weighted avg 0.00 0.02 0.00 99395
Accuracy: 0.023421701292821572
0.2
Treshold: 0.8
All
precision recall f1-score support
0 0.59 0.97 0.73 24893266
1 0.83 0.17 0.28 20563095
accuracy 0.61 45456361
macro avg 0.71 0.57 0.51 45456361
weighted avg 0.69 0.61 0.53 45456361
Accuracy: 0.6085714824378484
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.00 0.01 3872
accuracy 1.00 4877461
macro avg 0.53 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991608338846789
1-10%
precision recall f1-score support
0 0.69 0.98 0.81 16949103
1 0.62 0.06 0.11 8016772
accuracy 0.69 24965875
macro avg 0.65 0.52 0.46 24965875
weighted avg 0.67 0.69 0.59 24965875
Accuracy: 0.6863939677660006
10-20%
precision recall f1-score support
0 0.28 0.90 0.43 2057494
1 0.79 0.15 0.25 5461156
accuracy 0.35 7518650
macro avg 0.54 0.52 0.34 7518650
weighted avg 0.66 0.35 0.30 7518650
Accuracy: 0.3544235999813796
20-40%
precision recall f1-score support
0 0.17 0.81 0.28 744974
1 0.88 0.26 0.40 4060539
accuracy 0.35 4805513
macro avg 0.52 0.53 0.34 4805513
weighted avg 0.77 0.35 0.38 4805513
Accuracy: 0.34678961434502414
40-80%
precision recall f1-score support
0 0.10 0.72 0.17 235909
1 0.93 0.37 0.53 2483775
accuracy 0.40 2719684
macro avg 0.51 0.54 0.35 2719684
weighted avg 0.86 0.40 0.49 2719684
Accuracy: 0.39642436400699493
80-90%
precision recall f1-score support
0 0.07 0.68 0.12 18577
1 0.95 0.41 0.57 296772
accuracy 0.43 315349
macro avg 0.51 0.54 0.35 315349
weighted avg 0.90 0.43 0.55 315349
Accuracy: 0.4260454290325956
90-100%
precision recall f1-score support
0 0.06 0.67 0.11 13620
1 0.96 0.42 0.58 240209
accuracy 0.43 253829
macro avg 0.51 0.54 0.35 253829
weighted avg 0.91 0.43 0.56 253829
Accuracy: 0.4328110657174712
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.00 0.00 0.00 20563095
accuracy 0.55 45456361
macro avg 0.27 0.50 0.35 45456361
weighted avg 0.30 0.55 0.39 45456361
Accuracy: 0.5476299785633962
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.00 0.00 0.00 3872
accuracy 1.00 4877461
macro avg 0.50 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9992061443443627
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.00 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.34 0.50 0.40 24965875
weighted avg 0.46 0.68 0.55 24965875
Accuracy: 0.678890805950122
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.00 0.00 0.00 5461156
accuracy 0.27 7518650
macro avg 0.14 0.50 0.21 7518650
weighted avg 0.07 0.27 0.12 7518650
Accuracy: 0.2736520518976146
20-40%
precision recall f1-score support
0 0.16 1.00 0.27 744974
1 0.00 0.00 0.00 4060539
accuracy 0.16 4805513
macro avg 0.08 0.50 0.13 4805513
weighted avg 0.02 0.16 0.04 4805513
Accuracy: 0.15502486415082012
40-80%
precision recall f1-score support
0 0.09 1.00 0.16 235909
1 0.00 0.00 0.00 2483775
accuracy 0.09 2719684
macro avg 0.04 0.50 0.08 2719684
weighted avg 0.01 0.09 0.01 2719684
Accuracy: 0.08674132730126
80-90%
precision recall f1-score support
0 0.06 1.00 0.11 18577
1 0.00 0.00 0.00 296772
accuracy 0.06 315349
macro avg 0.03 0.50 0.06 315349
weighted avg 0.00 0.06 0.01 315349
Accuracy: 0.05890933537128705
90-100%
precision recall f1-score support
0 0.05 1.00 0.10 13620
1 0.00 0.00 0.00 240209
accuracy 0.05 253829
macro avg 0.03 0.50 0.05 253829
weighted avg 0.00 0.05 0.01 253829
Accuracy: 0.05365817144613105
0.4
Treshold: 0.8
All
precision recall f1-score support
0 0.62 0.96 0.76 22531902
1 0.82 0.23 0.36 16938696
accuracy 0.65 39470598
macro avg 0.72 0.60 0.56 39470598
weighted avg 0.71 0.65 0.59 39470598
Accuracy: 0.648759767967032
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 0.99 0.95 11439888
1 0.47 0.06 0.10 1271288
accuracy 0.90 12711176
macro avg 0.69 0.52 0.52 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.899239928705259
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.13 0.22 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.48 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5995566351011362
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.81 0.23 0.36 5583215
accuracy 0.47 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.66 0.47 0.43 8578813
Accuracy: 0.46709667176566266
40-80%
precision recall f1-score support
0 0.24 0.84 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.43 6296625
macro avg 0.56 0.58 0.42 6296625
weighted avg 0.75 0.43 0.45 6296625
Accuracy: 0.4279365533122903
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.42 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.42 0.47 810732
Accuracy: 0.41600306883162375
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.36 0.51 577496
accuracy 0.42 666440
macro avg 0.54 0.58 0.39 666440
weighted avg 0.82 0.42 0.48 666440
Accuracy: 0.41627303283116257
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.00 0.00 0.00 16938696
accuracy 0.57 39470598
macro avg 0.29 0.50 0.36 39470598
weighted avg 0.33 0.57 0.41 39470598
Accuracy: 0.5708528155565314
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 1.00 0.95 11439888
1 0.00 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.45 0.50 0.47 12711176
weighted avg 0.81 0.90 0.85 12711176
Accuracy: 0.8999865944740282
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.00 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.28 0.50 0.36 8856813
weighted avg 0.32 0.57 0.41 8856813
Accuracy: 0.5695548726161431
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.00 0.00 0.00 5583215
accuracy 0.35 8578813
macro avg 0.17 0.50 0.26 8578813
weighted avg 0.12 0.35 0.18 8578813
Accuracy: 0.34918560411562766
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.00 0.00 0.00 5001564
accuracy 0.21 6296625
macro avg 0.10 0.50 0.17 6296625
weighted avg 0.04 0.21 0.07 6296625
Accuracy: 0.20567542135667918
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.00 0.00 0.00 692761
accuracy 0.15 810732
macro avg 0.07 0.50 0.13 810732
weighted avg 0.02 0.15 0.04 810732
Accuracy: 0.14551171040491803
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.00 0.00 0.00 577496
accuracy 0.13 666440
macro avg 0.07 0.50 0.12 666440
weighted avg 0.02 0.13 0.03 666440
Accuracy: 0.13346137686813517
LR_9
0.01
Treshold: 0.8
All
precision recall f1-score support
0 0.60 0.99 0.75 28055468
1 0.91 0.14 0.25 21729815
accuracy 0.62 49785283
macro avg 0.76 0.57 0.50 49785283
weighted avg 0.74 0.62 0.53 49785283
Accuracy: 0.6201705833428727
0-1%
precision recall f1-score support
0 0.63 0.99 0.77 27764588
1 0.80 0.04 0.08 17098553
accuracy 0.63 44863141
macro avg 0.71 0.52 0.42 44863141
weighted avg 0.69 0.63 0.50 44863141
Accuracy: 0.6301739327614176
1-10%
precision recall f1-score support
0 0.07 0.58 0.13 287564
1 0.95 0.51 0.66 4164787
accuracy 0.51 4452351
macro avg 0.51 0.54 0.40 4452351
weighted avg 0.89 0.51 0.63 4452351
Accuracy: 0.5123178743095501
10-20%
precision recall f1-score support
0 0.01 0.25 0.02 2455
1 0.99 0.76 0.86 257616
accuracy 0.76 260071
macro avg 0.50 0.50 0.44 260071
weighted avg 0.98 0.76 0.85 260071
Accuracy: 0.7580083900165724
20-40%
precision recall f1-score support
0 0.01 0.36 0.01 659
1 1.00 0.67 0.80 130568
accuracy 0.66 131227
macro avg 0.50 0.51 0.40 131227
weighted avg 0.99 0.66 0.79 131227
Accuracy: 0.6647412498952198
40-80%
precision recall f1-score support
0 0.00 0.51 0.01 169
1 1.00 0.51 0.67 65234
accuracy 0.51 65403
macro avg 0.50 0.51 0.34 65403
weighted avg 0.99 0.51 0.67 65403
Accuracy: 0.5070409614237879
80-90%
precision recall f1-score support
0 0.00 0.60 0.00 15
1 1.00 0.40 0.57 7371
accuracy 0.40 7386
macro avg 0.50 0.50 0.29 7386
weighted avg 1.00 0.40 0.57 7386
Accuracy: 0.4018413214189006
90-100%
precision recall f1-score support
0 0.00 0.67 0.01 18
1 1.00 0.40 0.57 5686
accuracy 0.40 5704
macro avg 0.50 0.53 0.29 5704
weighted avg 0.99 0.40 0.57 5704
Accuracy: 0.39779102384291726
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 28055468
1 0.95 0.03 0.06 21729815
accuracy 0.58 49785283
macro avg 0.76 0.51 0.39 49785283
weighted avg 0.74 0.58 0.44 49785283
Accuracy: 0.5761586410988163
0-1%
precision recall f1-score support
0 0.62 1.00 0.76 27764588
1 0.55 0.00 0.00 17098553
accuracy 0.62 44863141
macro avg 0.59 0.50 0.38 44863141
weighted avg 0.59 0.62 0.47 44863141
Accuracy: 0.6189119928094201
1-10%
precision recall f1-score support
0 0.07 0.92 0.13 287564
1 0.96 0.13 0.24 4164787
accuracy 0.19 4452351
macro avg 0.51 0.53 0.18 4452351
weighted avg 0.90 0.19 0.23 4452351
Accuracy: 0.18560351598515032
10-20%
precision recall f1-score support
0 0.01 0.69 0.02 2455
1 0.99 0.30 0.47 257616
accuracy 0.31 260071
macro avg 0.50 0.50 0.24 260071
weighted avg 0.98 0.31 0.46 260071
Accuracy: 0.30831196096450586
20-40%
precision recall f1-score support
0 0.00 0.90 0.01 659
1 0.99 0.08 0.15 130568
accuracy 0.08 131227
macro avg 0.50 0.49 0.08 131227
weighted avg 0.99 0.08 0.15 131227
Accuracy: 0.08415950985696541
40-80%
precision recall f1-score support
0 0.00 1.00 0.01 169
1 1.00 0.00 0.00 65234
accuracy 0.00 65403
macro avg 0.50 0.50 0.00 65403
weighted avg 1.00 0.00 0.00 65403
Accuracy: 0.0038683240829931347
80-90%
precision recall f1-score support
0 0.00 1.00 0.00 15
1 0.00 0.00 0.00 7371
accuracy 0.00 7386
macro avg 0.00 0.50 0.00 7386
weighted avg 0.00 0.00 0.00 7386
Accuracy: 0.0020308692120227455
90-100%
precision recall f1-score support
0 0.00 1.00 0.01 18
1 0.00 0.00 0.00 5686
accuracy 0.00 5704
macro avg 0.00 0.50 0.00 5704
weighted avg 0.00 0.00 0.00 5704
Accuracy: 0.003155680224403927
0.1
Treshold: 0.8
All
precision recall f1-score support
0 0.58 0.98 0.73 26119367
1 0.85 0.15 0.26 21615229
accuracy 0.60 47734596
macro avg 0.72 0.56 0.49 47734596
weighted avg 0.70 0.60 0.51 47734596
Accuracy: 0.6032625687247882
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.25 0.01 0.02 508421
accuracy 0.96 12561431
macro avg 0.60 0.50 0.50 12561431
weighted avg 0.93 0.96 0.94 12561431
Accuracy: 0.9588855760143888
1-10%
precision recall f1-score support
0 0.49 0.97 0.65 13368467
1 0.72 0.07 0.12 14466820
accuracy 0.50 27835287
macro avg 0.60 0.52 0.39 27835287
weighted avg 0.61 0.50 0.38 27835287
Accuracy: 0.5011759713488854
10-20%
precision recall f1-score support
0 0.14 0.77 0.23 503365
1 0.89 0.27 0.41 3387274
accuracy 0.33 3890639
macro avg 0.51 0.52 0.32 3890639
weighted avg 0.79 0.33 0.39 3890639
Accuracy: 0.33145146594171293
20-40%
precision recall f1-score support
0 0.07 0.63 0.13 147488
1 0.94 0.41 0.57 1970425
accuracy 0.43 2117913
macro avg 0.51 0.52 0.35 2117913
weighted avg 0.88 0.43 0.54 2117913
Accuracy: 0.4257115377260539
40-80%
precision recall f1-score support
0 0.04 0.59 0.08 41616
1 0.97 0.45 0.62 1064279
accuracy 0.46 1105895
macro avg 0.50 0.52 0.35 1105895
weighted avg 0.93 0.46 0.60 1105895
Accuracy: 0.4593474063993417
80-90%
precision recall f1-score support
0 0.03 0.60 0.05 3093
1 0.98 0.45 0.62 120943
accuracy 0.46 124036
macro avg 0.50 0.53 0.34 124036
weighted avg 0.95 0.46 0.61 124036
Accuracy: 0.4583024283272598
90-100%
precision recall f1-score support
0 0.02 0.57 0.05 2328
1 0.98 0.45 0.62 97067
accuracy 0.45 99395
macro avg 0.50 0.51 0.33 99395
weighted avg 0.96 0.45 0.60 99395
Accuracy: 0.45403692338648827
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 26119367
1 0.00 0.00 0.00 21615229
accuracy 0.55 47734596
macro avg 0.27 0.50 0.35 47734596
weighted avg 0.30 0.55 0.39 47734596
Accuracy: 0.5471723275923399
0-1%
precision recall f1-score support
0 0.96 1.00 0.98 12053010
1 0.00 0.00 0.00 508421
accuracy 0.96 12561431
macro avg 0.48 0.50 0.49 12561431
weighted avg 0.92 0.96 0.94 12561431
Accuracy: 0.95949999645741
1-10%
precision recall f1-score support
0 0.48 1.00 0.65 13368467
1 0.00 0.00 0.00 14466820
accuracy 0.48 27835287
macro avg 0.24 0.50 0.32 27835287
weighted avg 0.23 0.48 0.31 27835287
Accuracy: 0.4802704926304514
10-20%
precision recall f1-score support
0 0.13 1.00 0.23 503365
1 0.00 0.00 0.00 3387274
accuracy 0.13 3890639
macro avg 0.06 0.50 0.11 3890639
weighted avg 0.02 0.13 0.03 3890639
Accuracy: 0.12937849026856513
20-40%
precision recall f1-score support
0 0.07 1.00 0.13 147488
1 0.00 0.00 0.00 1970425
accuracy 0.07 2117913
macro avg 0.03 0.50 0.07 2117913
weighted avg 0.00 0.07 0.01 2117913
Accuracy: 0.0696383656930195
40-80%
precision recall f1-score support
0 0.04 1.00 0.07 41616
1 0.00 0.00 0.00 1064279
accuracy 0.04 1105895
macro avg 0.02 0.50 0.04 1105895
weighted avg 0.00 0.04 0.00 1105895
Accuracy: 0.03763105900650604
80-90%
precision recall f1-score support
0 0.02 1.00 0.05 3093
1 0.00 0.00 0.00 120943
accuracy 0.02 124036
macro avg 0.01 0.50 0.02 124036
weighted avg 0.00 0.02 0.00 124036
Accuracy: 0.024936308813570254
90-100%
precision recall f1-score support
0 0.02 1.00 0.05 2328
1 0.00 0.00 0.00 97067
accuracy 0.02 99395
macro avg 0.01 0.50 0.02 99395
weighted avg 0.00 0.02 0.00 99395
Accuracy: 0.023421701292821572
0.2
Treshold: 0.8
All
precision recall f1-score support
0 0.59 0.97 0.73 24893266
1 0.83 0.17 0.28 20563095
accuracy 0.61 45456361
macro avg 0.71 0.57 0.50 45456361
weighted avg 0.69 0.61 0.53 45456361
Accuracy: 0.6076901976381259
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.05 0.00 0.01 3872
accuracy 1.00 4877461
macro avg 0.52 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9991612439340878
1-10%
precision recall f1-score support
0 0.69 0.98 0.81 16949103
1 0.62 0.06 0.11 8016772
accuracy 0.69 24965875
macro avg 0.65 0.52 0.46 24965875
weighted avg 0.67 0.69 0.59 24965875
Accuracy: 0.6862799321073265
10-20%
precision recall f1-score support
0 0.28 0.90 0.43 2057494
1 0.79 0.15 0.25 5461156
accuracy 0.35 7518650
macro avg 0.54 0.52 0.34 7518650
weighted avg 0.66 0.35 0.30 7518650
Accuracy: 0.3530458260458992
20-40%
precision recall f1-score support
0 0.17 0.81 0.28 744974
1 0.88 0.26 0.40 4060539
accuracy 0.34 4805513
macro avg 0.52 0.53 0.34 4805513
weighted avg 0.77 0.34 0.38 4805513
Accuracy: 0.34364738998729166
40-80%
precision recall f1-score support
0 0.10 0.72 0.17 235909
1 0.93 0.36 0.52 2483775
accuracy 0.39 2719684
macro avg 0.51 0.54 0.35 2719684
weighted avg 0.86 0.39 0.49 2719684
Accuracy: 0.39280519354454413
80-90%
precision recall f1-score support
0 0.07 0.68 0.12 18577
1 0.95 0.41 0.57 296772
accuracy 0.42 315349
macro avg 0.51 0.54 0.35 315349
weighted avg 0.90 0.42 0.54 315349
Accuracy: 0.42275383781144066
90-100%
precision recall f1-score support
0 0.06 0.67 0.11 13620
1 0.96 0.42 0.58 240209
accuracy 0.43 253829
macro avg 0.51 0.54 0.35 253829
weighted avg 0.91 0.43 0.55 253829
Accuracy: 0.4293638630731713
Treshold: 0.9
All
precision recall f1-score support
0 0.55 1.00 0.71 24893266
1 0.00 0.00 0.00 20563095
accuracy 0.55 45456361
macro avg 0.27 0.50 0.35 45456361
weighted avg 0.30 0.55 0.39 45456361
Accuracy: 0.5476299785633962
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 4873589
1 0.00 0.00 0.00 3872
accuracy 1.00 4877461
macro avg 0.50 0.50 0.50 4877461
weighted avg 1.00 1.00 1.00 4877461
Accuracy: 0.9992061443443627
1-10%
precision recall f1-score support
0 0.68 1.00 0.81 16949103
1 0.00 0.00 0.00 8016772
accuracy 0.68 24965875
macro avg 0.34 0.50 0.40 24965875
weighted avg 0.46 0.68 0.55 24965875
Accuracy: 0.678890805950122
10-20%
precision recall f1-score support
0 0.27 1.00 0.43 2057494
1 0.00 0.00 0.00 5461156
accuracy 0.27 7518650
macro avg 0.14 0.50 0.21 7518650
weighted avg 0.07 0.27 0.12 7518650
Accuracy: 0.2736520518976146
20-40%
precision recall f1-score support
0 0.16 1.00 0.27 744974
1 0.00 0.00 0.00 4060539
accuracy 0.16 4805513
macro avg 0.08 0.50 0.13 4805513
weighted avg 0.02 0.16 0.04 4805513
Accuracy: 0.15502486415082012
40-80%
precision recall f1-score support
0 0.09 1.00 0.16 235909
1 0.00 0.00 0.00 2483775
accuracy 0.09 2719684
macro avg 0.04 0.50 0.08 2719684
weighted avg 0.01 0.09 0.01 2719684
Accuracy: 0.08674132730126
80-90%
precision recall f1-score support
0 0.06 1.00 0.11 18577
1 0.00 0.00 0.00 296772
accuracy 0.06 315349
macro avg 0.03 0.50 0.06 315349
weighted avg 0.00 0.06 0.01 315349
Accuracy: 0.05890933537128705
90-100%
precision recall f1-score support
0 0.05 1.00 0.10 13620
1 0.00 0.00 0.00 240209
accuracy 0.05 253829
macro avg 0.03 0.50 0.05 253829
weighted avg 0.00 0.05 0.01 253829
Accuracy: 0.05365817144613105
0.4
Treshold: 0.8
All
precision recall f1-score support
0 0.62 0.96 0.76 22531902
1 0.82 0.23 0.36 16938696
accuracy 0.65 39470598
macro avg 0.72 0.60 0.56 39470598
weighted avg 0.71 0.65 0.59 39470598
Accuracy: 0.6486366130049511
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 0.99 0.95 11439888
1 0.47 0.06 0.10 1271288
accuracy 0.90 12711176
macro avg 0.69 0.52 0.52 12711176
weighted avg 0.86 0.90 0.86 12711176
Accuracy: 0.8992405580726756
10-20%
precision recall f1-score support
0 0.59 0.95 0.73 5044441
1 0.68 0.13 0.22 3812372
accuracy 0.60 8856813
macro avg 0.64 0.54 0.48 8856813
weighted avg 0.63 0.60 0.51 8856813
Accuracy: 0.5995083107207977
20-40%
precision recall f1-score support
0 0.39 0.90 0.54 2995598
1 0.81 0.23 0.36 5583215
accuracy 0.47 8578813
macro avg 0.60 0.57 0.45 8578813
weighted avg 0.66 0.47 0.43 8578813
Accuracy: 0.46689093234693424
40-80%
precision recall f1-score support
0 0.24 0.84 0.38 1295061
1 0.89 0.32 0.47 5001564
accuracy 0.43 6296625
macro avg 0.56 0.58 0.42 6296625
weighted avg 0.75 0.43 0.45 6296625
Accuracy: 0.42760097671371566
80-90%
precision recall f1-score support
0 0.18 0.82 0.29 117971
1 0.92 0.35 0.50 692761
accuracy 0.42 810732
macro avg 0.55 0.58 0.40 810732
weighted avg 0.81 0.42 0.47 810732
Accuracy: 0.41565770192862744
90-100%
precision recall f1-score support
0 0.16 0.81 0.27 88944
1 0.92 0.36 0.51 577496
accuracy 0.42 666440
macro avg 0.54 0.58 0.39 666440
weighted avg 0.82 0.42 0.48 666440
Accuracy: 0.4158483884520737
Treshold: 0.9
All
precision recall f1-score support
0 0.57 1.00 0.73 22531902
1 0.00 0.00 0.00 16938696
accuracy 0.57 39470598
macro avg 0.29 0.50 0.36 39470598
weighted avg 0.33 0.57 0.41 39470598
Accuracy: 0.5708528155565314
0-1%
precision recall f1-score support
0 1.00 1.00 1.00 1549999
accuracy 1.00 1549999
macro avg 1.00 1.00 1.00 1549999
weighted avg 1.00 1.00 1.00 1549999
Accuracy: 1.0
1-10%
precision recall f1-score support
0 0.90 1.00 0.95 11439888
1 0.00 0.00 0.00 1271288
accuracy 0.90 12711176
macro avg 0.45 0.50 0.47 12711176
weighted avg 0.81 0.90 0.85 12711176
Accuracy: 0.8999865944740282
10-20%
precision recall f1-score support
0 0.57 1.00 0.73 5044441
1 0.00 0.00 0.00 3812372
accuracy 0.57 8856813
macro avg 0.28 0.50 0.36 8856813
weighted avg 0.32 0.57 0.41 8856813
Accuracy: 0.5695548726161431
20-40%
precision recall f1-score support
0 0.35 1.00 0.52 2995598
1 0.00 0.00 0.00 5583215
accuracy 0.35 8578813
macro avg 0.17 0.50 0.26 8578813
weighted avg 0.12 0.35 0.18 8578813
Accuracy: 0.34918560411562766
40-80%
precision recall f1-score support
0 0.21 1.00 0.34 1295061
1 0.00 0.00 0.00 5001564
accuracy 0.21 6296625
macro avg 0.10 0.50 0.17 6296625
weighted avg 0.04 0.21 0.07 6296625
Accuracy: 0.20567542135667918
80-90%
precision recall f1-score support
0 0.15 1.00 0.25 117971
1 0.00 0.00 0.00 692761
accuracy 0.15 810732
macro avg 0.07 0.50 0.13 810732
weighted avg 0.02 0.15 0.04 810732
Accuracy: 0.14551171040491803
90-100%
precision recall f1-score support
0 0.13 1.00 0.24 88944
1 0.00 0.00 0.00 577496
accuracy 0.13 666440
macro avg 0.07 0.50 0.12 666440
weighted avg 0.02 0.13 0.03 666440
Accuracy: 0.13346137686813517
Individual Workload Result
zipf_1_15
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6046758 | 0.403719 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| Zipf Optimal Distribution | 9519768 | 0.404397 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9773902 | 0.404839 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9740182 | 0.404872 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9723106 | 0.404903 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10298833 | 0.405037 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10299939 | 0.405037 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10300318 | 0.40504 | ../../result/log/zipf_1_15 | 0.01 | 1 |
| Offline Clock 1st iteration | 10440959 | 0.405173 | ../../result/log/zipf_1_15 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5855919 | 0.209857 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| Zipf Optimal Distribution | 8927244 | 0.211885 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9749804 | 0.213586 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9741455 | 0.213588 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9737587 | 0.213589 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10273491 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10273489 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| Offline Clock 1st iteration | 10273545 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10273491 | 0.213817 | ../../result/log/zipf_1_15 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5679810 | 0.147307 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| Zipf Optimal Distribution | 8496578 | 0.150203 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| Offline Clock 1st iteration | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10000415 | 0.15275 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9531967 | 0.152768 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9531595 | 0.152769 | ../../result/log/zipf_1_15 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9517061 | 0.15277 | ../../result/log/zipf_1_15 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5220469 | 0.0827401 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| Zipf Optimal Distribution | 7658498 | 0.0867334 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| Offline Clock 1st iteration | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9234422 | 0.0897434 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8605042 | 0.0898638 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8604425 | 0.0898642 | ../../result/log/zipf_1_15 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8604072 | 0.0898644 | ../../result/log/zipf_1_15 | 0.4 | 1 |
zipf_1_16
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6044928 | 0.403882 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| Zipf Optimal Distribution | 9516893 | 0.40457 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9769605 | 0.405016 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9736498 | 0.405046 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9719385 | 0.405075 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10295691 | 0.405206 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10296736 | 0.405207 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10297041 | 0.405209 | ../../result/log/zipf_1_16 | 0.01 | 1 |
| Offline Clock 1st iteration | 10437637 | 0.405347 | ../../result/log/zipf_1_16 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5851636 | 0.210029 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| Zipf Optimal Distribution | 8926367 | 0.212052 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9750736 | 0.213751 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9743143 | 0.213754 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9739734 | 0.213755 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| Offline Clock 1st iteration | 10274590 | 0.213983 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10274532 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10274534 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10274534 | 0.213984 | ../../result/log/zipf_1_16 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5683642 | 0.147393 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| Zipf Optimal Distribution | 8505430 | 0.150288 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| Offline Clock 1st iteration | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10010518 | 0.152836 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9547859 | 0.152851 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9547489 | 0.152852 | ../../result/log/zipf_1_16 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9535780 | 0.152853 | ../../result/log/zipf_1_16 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5225924 | 0.0827439 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| Zipf Optimal Distribution | 7664562 | 0.0867505 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| Offline Clock 1st iteration | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9242882 | 0.0897459 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8611294 | 0.0898878 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8610365 | 0.0898882 | ../../result/log/zipf_1_16 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8610028 | 0.0898884 | ../../result/log/zipf_1_16 | 0.4 | 1 |
zipf_1_17
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6046350 | 0.403777 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| Zipf Optimal Distribution | 9518366 | 0.404457 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9771886 | 0.404899 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9738418 | 0.404932 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9721381 | 0.404961 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10297456 | 0.405097 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10298403 | 0.405097 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10298864 | 0.405099 | ../../result/log/zipf_1_17 | 0.01 | 1 |
| Offline Clock 1st iteration | 10439561 | 0.405242 | ../../result/log/zipf_1_17 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5851791 | 0.209897 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| Zipf Optimal Distribution | 8925674 | 0.211925 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9747434 | 0.213628 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.8] | 9739230 | 0.21363 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9735705 | 0.213631 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10272576 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10272574 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| Offline Clock 1st iteration | 10272630 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10272576 | 0.213852 | ../../result/log/zipf_1_17 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5680729 | 0.147336 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| Zipf Optimal Distribution | 8498188 | 0.150231 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| Offline Clock 1st iteration | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10002880 | 0.152785 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9523014 | 0.152804 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9536570 | 0.152804 | ../../result/log/zipf_1_17 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9536275 | 0.152805 | ../../result/log/zipf_1_17 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5224778 | 0.0827112 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| Zipf Optimal Distribution | 7661751 | 0.0867151 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| Offline Clock 1st iteration | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9240697 | 0.0897079 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8607827 | 0.0898513 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8608122 | 0.0898514 | ../../result/log/zipf_1_17 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8608694 | 0.0898514 | ../../result/log/zipf_1_17 | 0.4 | 1 |
zipf_1_18
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6046061 | 0.40372 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| Zipf Optimal Distribution | 9518058 | 0.404413 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9772939 | 0.404858 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9739576 | 0.404889 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9722629 | 0.404917 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10298097 | 0.405058 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10299138 | 0.405058 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10299781 | 0.405059 | ../../result/log/zipf_1_18 | 0.01 | 1 |
| Offline Clock 1st iteration | 10439737 | 0.4052 | ../../result/log/zipf_1_18 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5852167 | 0.209865 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| Zipf Optimal Distribution | 8924501 | 0.211883 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9741672 | 0.213594 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9730334 | 0.213597 | ../../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 |
| Offline Clock 1st iteration | 10268394 | 0.213821 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10268336 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10268337 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10268339 | 0.213822 | ../../result/log/zipf_1_18 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5677502 | 0.147262 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| Zipf Optimal Distribution | 8501025 | 0.150135 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| Offline Clock 1st iteration | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10001082 | 0.152706 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9518277 | 0.152725 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9531160 | 0.152725 | ../../result/log/zipf_1_18 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9530717 | 0.152726 | ../../result/log/zipf_1_18 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5223361 | 0.0826611 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| Zipf Optimal Distribution | 7661309 | 0.0866641 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| Offline Clock 1st iteration | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9239322 | 0.0896548 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8606890 | 0.0897961 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8606269 | 0.0897963 | ../../result/log/zipf_1_18 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8605948 | 0.0897965 | ../../result/log/zipf_1_18 | 0.4 | 1 |
zipf_1_19
Ignore Obj Size
0.01
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 6047379 | 0.403776 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| Zipf Optimal Distribution | 9518278 | 0.404475 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.8] | 9774585 | 0.404917 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.8] | 9740851 | 0.404951 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.8] | 9724440 | 0.404975 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_8[cache_size=0.01,treshold=0.9] | 10300967 | 0.405117 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_9[cache_size=0.01,treshold=0.9] | 10302179 | 0.405117 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| LR_7[cache_size=0.01,treshold=0.9] | 10302521 | 0.405119 | ../../result/log/zipf_1_19 | 0.01 | 1 |
| Offline Clock 1st iteration | 10442800 | 0.405256 | ../../result/log/zipf_1_19 | 0.01 | 1 |
0.1
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5852464 | 0.209927 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| Zipf Optimal Distribution | 8923837 | 0.21197 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.8] | 9745686 | 0.213665 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.8] | 9734226 | 0.213668 | ../../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 |
| Offline Clock 1st iteration | 10270642 | 0.213882 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_8[cache_size=0.1,treshold=0.9] | 10270587 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_7[cache_size=0.1,treshold=0.9] | 10270590 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
| LR_9[cache_size=0.1,treshold=0.9] | 10270589 | 0.213883 | ../../result/log/zipf_1_19 | 0.1 | 1 |
0.2
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5678610 | 0.147359 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| Zipf Optimal Distribution | 8501803 | 0.150225 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.9] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| Offline Clock 1st iteration | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.9] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.9] | 10003476 | 0.152791 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_8[cache_size=0.2,treshold=0.8] | 9527439 | 0.152809 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_7[cache_size=0.2,treshold=0.8] | 9540045 | 0.15281 | ../../result/log/zipf_1_19 | 0.2 | 1 |
| LR_9[cache_size=0.2,treshold=0.8] | 9539643 | 0.152811 | ../../result/log/zipf_1_19 | 0.2 | 1 |
0.4
| Model | Promotion | Miss Ratio | Trace | Cache Size | Ignore Obj Size |
|---|
| Offline Clock 2nd iteration | 5227240 | 0.0827181 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| Zipf Optimal Distribution | 7662557 | 0.0867323 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.9] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| Offline Clock 1st iteration | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.9] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.9] | 9241538 | 0.0897029 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_9[cache_size=0.4,treshold=0.8] | 8613404 | 0.0898297 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_7[cache_size=0.4,treshold=0.8] | 8612834 | 0.0898298 | ../../result/log/zipf_1_19 | 0.4 | 1 |
| LR_8[cache_size=0.4,treshold=0.8] | 8612504 | 0.0898298 | ../../result/log/zipf_1_19 | 0.4 | 1 |