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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

30
reports/WeightFiltration/attack_values.csv
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@@ -3,3 +3,33 @@ target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
1,0.500000,1.279257,0.968750
2,0.500000,1.717911,0.937500
3,0.500000,1.354225,0.989583
4,0.500000,1.308562,0.968750
5,0.500000,2.087495,0.947917
6,0.500000,1.793863,0.927083
7,0.500000,1.213634,0.937500
8,0.500000,1.705230,0.979167
9,0.500000,1.713113,0.979167
10,0.500000,1.358761,0.968750
11,0.500000,1.485312,1.000000
12,0.500000,1.393625,0.947917
13,0.500000,1.677361,0.947917
14,0.500000,1.734759,0.906250
15,0.500000,1.715959,0.968750
16,0.500000,1.180073,0.947917
17,0.500000,1.597037,0.947917
18,0.500000,1.491600,0.947917
19,0.500000,1.622301,0.968750
0,0.500000,1.562955,0.968750
0,0.500000,1.526132,0.979167
1,0.500000,1.323757,0.968750
2,0.500000,1.493928,0.958333
3,0.500000,1.643880,0.989583
4,0.500000,1.479018,0.989583
5,0.500000,2.176565,0.958333
6,0.500000,1.620670,0.958333
7,0.500000,0.977823,0.937500
8,0.500000,1.455012,0.968750
9,0.500000,2.145126,0.989583
10,0.500000,1.905214,0.895833
11,0.500000,2.171935,0.958333
12,0.500000,1.761187,0.937500
1 target_class parameter_mia_accuracy latent_distance_tell lookalike_accuracy
3 1 0.500000 1.279257 0.968750
4 2 0.500000 1.717911 0.937500
5 3 0.500000 1.354225 0.989583
6 4 0.500000 1.308562 0.968750
7 5 0.500000 2.087495 0.947917
8 6 0.500000 1.793863 0.927083
9 7 0.500000 1.213634 0.937500
10 8 0.500000 1.705230 0.979167
11 9 0.500000 1.713113 0.979167
12 10 0.500000 1.358761 0.968750
13 11 0.500000 1.485312 1.000000
14 12 0.500000 1.393625 0.947917
15 13 0.500000 1.677361 0.947917
16 14 0.500000 1.734759 0.906250
17 15 0.500000 1.715959 0.968750
18 16 0.500000 1.180073 0.947917
19 17 0.500000 1.597037 0.947917
20 18 0.500000 1.491600 0.947917
21 19 0.500000 1.622301 0.968750
22 0 0.500000 1.562955 0.968750
23 0 0.500000 1.526132 0.979167
24 1 0.500000 1.323757 0.968750
25 2 0.500000 1.493928 0.958333
26 3 0.500000 1.643880 0.989583
27 4 0.500000 1.479018 0.989583
28 5 0.500000 2.176565 0.958333
29 6 0.500000 1.620670 0.958333
30 7 0.500000 0.977823 0.937500
31 8 0.500000 1.455012 0.968750
32 9 0.500000 2.145126 0.989583
33 10 0.500000 1.905214 0.895833
34 11 0.500000 2.171935 0.958333
35 12 0.500000 1.761187 0.937500