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Tinsae
2026-07-08 10:07:39 +02:00
parent eb8060fc05
commit a118a975c1
20 changed files with 287 additions and 22 deletions
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12
reports/WeightFiltration/RESNET34/forget.csv
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@@ -527,3 +527,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0375,1.0000,0.0375,0.0723,1.0000,0.0375,0.0723
0.1750,1.0000,0.1750,0.2979,1.0000,0.1750,0.2979
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0375,1.0000,0.0375,0.0723,1.0000,0.0375,0.0723
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
527 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
528 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
529 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
530 0.0375 1.0000 0.0375 0.0723 1.0000 0.0375 0.0723
531 0.1750 1.0000 0.1750 0.2979 1.0000 0.1750 0.2979
532 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
533 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
534 0.0375 1.0000 0.0375 0.0723 1.0000 0.0375 0.0723
535 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
536 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
537 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
538 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
539 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
540 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
541 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

12
reports/WeightFiltration/RESNET34/forget_train.csv
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@@ -527,3 +527,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0375,1.0000,0.0375,0.0723,1.0000,0.0375,0.0723
0.2281,1.0000,0.2281,0.3715,1.0000,0.2281,0.3715
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0094,1.0000,0.0094,0.0186,1.0000,0.0094,0.0186
0.0094,1.0000,0.0094,0.0186,1.0000,0.0094,0.0186
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0063,1.0000,0.0063,0.0124,1.0000,0.0063,0.0124
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
527 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
528 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
529 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
530 0.0375 1.0000 0.0375 0.0723 1.0000 0.0375 0.0723
531 0.2281 1.0000 0.2281 0.3715 1.0000 0.2281 0.3715
532 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
533 0.0094 1.0000 0.0094 0.0186 1.0000 0.0094 0.0186
534 0.0094 1.0000 0.0094 0.0186 1.0000 0.0094 0.0186
535 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
536 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
537 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
538 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
539 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
540 0.0063 1.0000 0.0063 0.0124 1.0000 0.0063 0.0124
541 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

12
reports/WeightFiltration/RESNET34/retain.csv
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@@ -527,3 +527,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.9546,0.9558,0.9546,0.9547,0.9558,0.9546,0.9547
0.9526,0.9540,0.9526,0.9528,0.9540,0.9526,0.9528
0.9526,0.9540,0.9526,0.9528,0.9540,0.9526,0.9528
0.9520,0.9541,0.9520,0.9524,0.9541,0.9520,0.9524
0.9520,0.9542,0.9520,0.9524,0.9542,0.9520,0.9524
0.9507,0.9515,0.9507,0.9507,0.9515,0.9507,0.9507
0.9533,0.9548,0.9533,0.9535,0.9548,0.9533,0.9535
0.9566,0.9583,0.9566,0.9569,0.9583,0.9566,0.9569
0.9572,0.9588,0.9572,0.9574,0.9588,0.9572,0.9574
0.9533,0.9551,0.9533,0.9536,0.9551,0.9533,0.9536
0.9487,0.9518,0.9487,0.9493,0.9518,0.9487,0.9493
0.9546,0.9559,0.9546,0.9547,0.9559,0.9546,0.9547
0.9520,0.9534,0.9520,0.9522,0.9534,0.9520,0.9522
0.9539,0.9554,0.9539,0.9542,0.9554,0.9539,0.9542
0.9539,0.9559,0.9539,0.9543,0.9559,0.9539,0.9543
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
527 0.9546 0.9558 0.9546 0.9547 0.9558 0.9546 0.9547
528 0.9526 0.9540 0.9526 0.9528 0.9540 0.9526 0.9528
529 0.9526 0.9540 0.9526 0.9528 0.9540 0.9526 0.9528
530 0.9520 0.9541 0.9520 0.9524 0.9541 0.9520 0.9524
531 0.9520 0.9542 0.9520 0.9524 0.9542 0.9520 0.9524
532 0.9507 0.9515 0.9507 0.9507 0.9515 0.9507 0.9507
533 0.9533 0.9548 0.9533 0.9535 0.9548 0.9533 0.9535
534 0.9566 0.9583 0.9566 0.9569 0.9583 0.9566 0.9569
535 0.9572 0.9588 0.9572 0.9574 0.9588 0.9572 0.9574
536 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
537 0.9487 0.9518 0.9487 0.9493 0.9518 0.9487 0.9493
538 0.9546 0.9559 0.9546 0.9547 0.9559 0.9546 0.9547
539 0.9520 0.9534 0.9520 0.9522 0.9534 0.9520 0.9522
540 0.9539 0.9554 0.9539 0.9542 0.9554 0.9539 0.9542
541 0.9539 0.9559 0.9539 0.9543 0.9559 0.9539 0.9543