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cleaned up code

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Tinsae
2026-07-08 23:53:07 +02:00
parent 31f461342e
commit 04875a62e9
23 changed files with 1362 additions and 715 deletions
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61
reports/LinearFiltration/RESNET34/forget.csv
View File

@@ -450,3 +450,64 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
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61
reports/LinearFiltration/RESNET34/forget_train.csv
View File

@@ -450,3 +450,64 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
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61
reports/LinearFiltration/RESNET34/retain.csv
View File

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0.9566,0.9581,0.9566,0.9568,0.9581,0.9566,0.9568
0.9553,0.9568,0.9553,0.9555,0.9568,0.9553,0.9555
0.9513,0.9532,0.9513,0.9516,0.9532,0.9513,0.9516
0.9539,0.9556,0.9539,0.9542,0.9556,0.9539,0.9542
0.9520,0.9539,0.9520,0.9523,0.9539,0.9520,0.9523
0.9533,0.9547,0.9533,0.9535,0.9547,0.9533,0.9535
0.9546,0.9561,0.9546,0.9549,0.9561,0.9546,0.9549
0.9513,0.9531,0.9513,0.9516,0.9531,0.9513,0.9516
0.9533,0.9549,0.9533,0.9535,0.9549,0.9533,0.9535
0.9559,0.9570,0.9559,0.9561,0.9570,0.9559,0.9561
0.9513,0.9532,0.9513,0.9516,0.9532,0.9513,0.9516
0.9513,0.9531,0.9513,0.9516,0.9531,0.9513,0.9516
0.9520,0.9538,0.9520,0.9523,0.9538,0.9520,0.9523
0.9539,0.9554,0.9539,0.9542,0.9554,0.9539,0.9542
0.9526,0.9544,0.9526,0.9529,0.9544,0.9526,0.9529
0.9526,0.9541,0.9526,0.9529,0.9541,0.9526,0.9529
0.9533,0.9551,0.9533,0.9536,0.9551,0.9533,0.9536
0.9533,0.9545,0.9533,0.9535,0.9545,0.9533,0.9535
0.9546,0.9562,0.9546,0.9548,0.9562,0.9546,0.9548
0.9526,0.9541,0.9526,0.9529,0.9541,0.9526,0.9529
0.9526,0.9541,0.9526,0.9529,0.9541,0.9526,0.9529
0.9533,0.9551,0.9533,0.9536,0.9551,0.9533,0.9536
0.9533,0.9545,0.9533,0.9535,0.9545,0.9533,0.9535
0.9546,0.9562,0.9546,0.9548,0.9562,0.9546,0.9548
0.9526,0.9541,0.9526,0.9529,0.9541,0.9526,0.9529
0.9533,0.9551,0.9533,0.9536,0.9551,0.9533,0.9536
0.9533,0.9545,0.9533,0.9535,0.9545,0.9533,0.9535
0.9546,0.9562,0.9546,0.9548,0.9562,0.9546,0.9548
0.9553,0.9570,0.9553,0.9555,0.9570,0.9553,0.9555
0.9566,0.9581,0.9566,0.9568,0.9581,0.9566,0.9568
0.9553,0.9568,0.9553,0.9555,0.9568,0.9553,0.9555
0.9513,0.9532,0.9513,0.9516,0.9532,0.9513,0.9516
0.9539,0.9556,0.9539,0.9542,0.9556,0.9539,0.9542
0.9520,0.9539,0.9520,0.9523,0.9539,0.9520,0.9523
0.9533,0.9547,0.9533,0.9535,0.9547,0.9533,0.9535
0.9546,0.9561,0.9546,0.9549,0.9561,0.9546,0.9549
0.9513,0.9531,0.9513,0.9516,0.9531,0.9513,0.9516
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
450 0.9533 0.9547 0.9533 0.9535 0.9547 0.9533 0.9535
451 0.9546 0.9561 0.9546 0.9549 0.9561 0.9546 0.9549
452 0.9513 0.9531 0.9513 0.9516 0.9531 0.9513 0.9516
453 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
454 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
455 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
456 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
457 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
458 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
459 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
460 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
461 0.9546 0.9562 0.9546 0.9548 0.9562 0.9546 0.9548
462 0.9553 0.9570 0.9553 0.9555 0.9570 0.9553 0.9555
463 0.9566 0.9581 0.9566 0.9568 0.9581 0.9566 0.9568
464 0.9553 0.9568 0.9553 0.9555 0.9568 0.9553 0.9555
465 0.9513 0.9532 0.9513 0.9516 0.9532 0.9513 0.9516
466 0.9539 0.9556 0.9539 0.9542 0.9556 0.9539 0.9542
467 0.9520 0.9539 0.9520 0.9523 0.9539 0.9520 0.9523
468 0.9533 0.9547 0.9533 0.9535 0.9547 0.9533 0.9535
469 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
470 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
471 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
472 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
473 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
474 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
475 0.9546 0.9562 0.9546 0.9548 0.9562 0.9546 0.9548
476 0.9553 0.9570 0.9553 0.9555 0.9570 0.9553 0.9555
477 0.9566 0.9581 0.9566 0.9568 0.9581 0.9566 0.9568
478 0.9553 0.9568 0.9553 0.9555 0.9568 0.9553 0.9555
479 0.9513 0.9532 0.9513 0.9516 0.9532 0.9513 0.9516
480 0.9539 0.9556 0.9539 0.9542 0.9556 0.9539 0.9542
481 0.9520 0.9539 0.9520 0.9523 0.9539 0.9520 0.9523
482 0.9533 0.9547 0.9533 0.9535 0.9547 0.9533 0.9535
483 0.9546 0.9561 0.9546 0.9549 0.9561 0.9546 0.9549
484 0.9513 0.9531 0.9513 0.9516 0.9531 0.9513 0.9516
485 0.9533 0.9549 0.9533 0.9535 0.9549 0.9533 0.9535
486 0.9559 0.9570 0.9559 0.9561 0.9570 0.9559 0.9561
487 0.9513 0.9532 0.9513 0.9516 0.9532 0.9513 0.9516
488 0.9513 0.9531 0.9513 0.9516 0.9531 0.9513 0.9516
489 0.9520 0.9538 0.9520 0.9523 0.9538 0.9520 0.9523
490 0.9539 0.9554 0.9539 0.9542 0.9554 0.9539 0.9542
491 0.9526 0.9544 0.9526 0.9529 0.9544 0.9526 0.9529
492 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
493 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
494 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
495 0.9546 0.9562 0.9546 0.9548 0.9562 0.9546 0.9548
496 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
497 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
498 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
499 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
500 0.9546 0.9562 0.9546 0.9548 0.9562 0.9546 0.9548
501 0.9526 0.9541 0.9526 0.9529 0.9541 0.9526 0.9529
502 0.9533 0.9551 0.9533 0.9536 0.9551 0.9533 0.9536
503 0.9533 0.9545 0.9533 0.9535 0.9545 0.9533 0.9535
504 0.9546 0.9562 0.9546 0.9548 0.9562 0.9546 0.9548
505 0.9553 0.9570 0.9553 0.9555 0.9570 0.9553 0.9555
506 0.9566 0.9581 0.9566 0.9568 0.9581 0.9566 0.9568
507 0.9553 0.9568 0.9553 0.9555 0.9568 0.9553 0.9555
508 0.9513 0.9532 0.9513 0.9516 0.9532 0.9513 0.9516
509 0.9539 0.9556 0.9539 0.9542 0.9556 0.9539 0.9542
510 0.9520 0.9539 0.9520 0.9523 0.9539 0.9520 0.9523
511 0.9533 0.9547 0.9533 0.9535 0.9547 0.9533 0.9535
512 0.9546 0.9561 0.9546 0.9549 0.9561 0.9546 0.9549
513 0.9513 0.9531 0.9513 0.9516 0.9531 0.9513 0.9516

73
reports/LinearFiltration/attack_values.csv
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@@ -1,35 +1,38 @@
target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
0,0.500000,3.219560,1.000000
1,0.500000,3.573733,1.000000
2,0.500000,3.924550,1.000000
3,0.500000,3.515182,1.000000
4,0.500000,3.369485,1.000000
5,0.500000,4.697085,1.000000
6,0.500000,4.185269,1.000000
7,0.500000,3.473583,1.000000
8,0.500000,4.518519,1.000000
9,0.500000,4.484542,1.000000
10,0.500000,3.353875,1.000000
11,0.500000,3.815037,0.989583
12,0.500000,3.493994,1.000000
13,0.500000,4.018041,1.000000
14,0.500000,4.059689,1.000000
15,0.500000,4.097189,1.000000
16,0.500000,3.287521,1.000000
17,0.500000,3.872488,1.000000
18,0.500000,3.698952,0.989583
19,0.500000,3.844830,0.989583
0,0.500000,3.413494,1.000000
0,0.500000,3.416399,1.000000
1,0.500000,3.396268,1.000000
2,0.500000,3.648122,1.000000
3,0.500000,3.889339,0.989583
4,0.500000,3.408539,1.000000
5,0.500000,4.625342,1.000000
6,0.500000,3.925502,0.989583
7,0.500000,3.033561,0.989583
8,0.500000,3.819170,0.989583
9,0.500000,4.497495,1.000000
10,0.500000,3.701839,1.000000
11,0.500000,4.369391,0.989583
12,0.500000,3.945474,1.000000
target_class, parameter_mia_accuracy, lookalike_accuracy, A-Dist, JS-Dist
0,0.500000,1.000000, 0.062500, 0.485899
1,0.500000,1.000000, 0.083333, 0.484178
2,0.500000,0.989583, 0.010417, 0.525418
3,0.500000,0.989583, 0.333333, 0.487282
4,0.500000,1.000000, 0.020833, 0.505002
5,0.500000,1.000000, 0.093750, 0.491621
6,0.500000,1.000000, 0.052083, 0.482068
7,0.500000,0.979167, 0.010417, 0.519800
8,0.500000,0.989583, 0.020833, 0.485863
9,0.500000,0.989583, 0.208333, 0.483455
10,0.500000,1.000000, 0.145833, 0.454615
11,0.500000,1.000000, 0.333333, 0.495618
12,0.500000,1.000000, 0.072917, 0.458427
13,0.500000,1.000000, 0.135417, 0.477052
14,0.500000,1.000000, 0.020833, 0.472611
15,0.500000,1.000000, 0.239583, 0.479607
16,0.500000,1.000000, 0.135417, 0.468667
17,0.500000,1.000000, 0.208333, 0.469592
18,0.500000,1.000000, 0.197917, 0.454318
19,0.500000,0.989583, 0.041667, 0.499034
0,0.500000,1.000000, 0.072917, 0.483694
1,0.500000,1.000000, 0.239583, 0.482249
2,0.500000,0.989583, 0.062500, 0.528699
3,0.500000,1.000000, 0.177083, 0.488769
0,0.500000,1.000000, 0.208333, 0.479962
1,0.500000,1.000000, 0.177083, 0.480766
2,0.500000,1.000000, 0.156250, 0.530593
3,0.500000,1.000000, 0.031250, 0.490093
4,0.500000,1.000000, 0.062500, 0.514937
5,0.500000,1.000000, 0.041667, 0.483999
6,0.500000,1.000000, 0.041667, 0.480639
7,0.500000,1.000000, 0.114583, 0.516643
8,0.500000,1.000000, 0.322917, 0.482295
9,0.500000,1.000000, 0.156250, 0.482486
10,0.500000,1.000000, 0.208333, 0.454807
11,0.500000,1.000000, 0.197917, 0.496418
12,0.500000,1.000000, 0.083333, 0.449275
1 target_class parameter_mia_accuracy latent_distance_tell lookalike_accuracy A-Dist JS-Dist
2 0 0.500000 3.219560 1.000000 0.062500 0.485899
3 1 0.500000 3.573733 1.000000 0.083333 0.484178
4 2 0.500000 3.924550 1.000000 0.989583 0.010417 0.525418
5 3 0.500000 3.515182 1.000000 0.989583 0.333333 0.487282
6 4 0.500000 3.369485 1.000000 0.020833 0.505002
7 5 0.500000 4.697085 1.000000 0.093750 0.491621
8 6 0.500000 4.185269 1.000000 0.052083 0.482068
9 7 0.500000 3.473583 1.000000 0.979167 0.010417 0.519800
10 8 0.500000 4.518519 1.000000 0.989583 0.020833 0.485863
11 9 0.500000 4.484542 1.000000 0.989583 0.208333 0.483455
12 10 0.500000 3.353875 1.000000 0.145833 0.454615
13 11 0.500000 3.815037 0.989583 1.000000 0.333333 0.495618
14 12 0.500000 3.493994 1.000000 0.072917 0.458427
15 13 0.500000 4.018041 1.000000 0.135417 0.477052
16 14 0.500000 4.059689 1.000000 0.020833 0.472611
17 15 0.500000 4.097189 1.000000 0.239583 0.479607
18 16 0.500000 3.287521 1.000000 0.135417 0.468667
19 17 0.500000 3.872488 1.000000 0.208333 0.469592
20 18 0.500000 3.698952 0.989583 1.000000 0.197917 0.454318
21 19 0.500000 3.844830 0.989583 0.041667 0.499034
22 0 0.500000 3.413494 1.000000 0.072917 0.483694
23 0 1 0.500000 3.416399 1.000000 0.239583 0.482249
24 1 2 0.500000 3.396268 1.000000 0.989583 0.062500 0.528699
25 2 3 0.500000 3.648122 1.000000 0.177083 0.488769
26 3 0 0.500000 3.889339 0.989583 1.000000 0.208333 0.479962
27 4 1 0.500000 3.408539 1.000000 0.177083 0.480766
28 5 2 0.500000 4.625342 1.000000 0.156250 0.530593
29 6 3 0.500000 3.925502 0.989583 1.000000 0.031250 0.490093
30 7 4 0.500000 3.033561 0.989583 1.000000 0.062500 0.514937
31 8 5 0.500000 3.819170 0.989583 1.000000 0.041667 0.483999
32 9 6 0.500000 4.497495 1.000000 0.041667 0.480639
33 10 7 0.500000 3.701839 1.000000 0.114583 0.516643
34 11 8 0.500000 4.369391 0.989583 1.000000 0.322917 0.482295
35 12 9 0.500000 3.945474 1.000000 0.156250 0.482486
36 10 0.500000 1.000000 0.208333 0.454807
37 11 0.500000 1.000000 0.197917 0.496418
38 12 0.500000 1.000000 0.083333 0.449275

35
reports/LinearFiltration/attack_values_int.csv Normal file
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@@ -0,0 +1,35 @@
target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
0,0.500000,3.219560,1.000000
1,0.500000,3.573733,1.000000
2,0.500000,3.924550,1.000000
3,0.500000,3.515182,1.000000
4,0.500000,3.369485,1.000000
5,0.500000,4.697085,1.000000
6,0.500000,4.185269,1.000000
7,0.500000,3.473583,1.000000
8,0.500000,4.518519,1.000000
9,0.500000,4.484542,1.000000
10,0.500000,3.353875,1.000000
11,0.500000,3.815037,0.989583
12,0.500000,3.493994,1.000000
13,0.500000,4.018041,1.000000
14,0.500000,4.059689,1.000000
15,0.500000,4.097189,1.000000
16,0.500000,3.287521,1.000000
17,0.500000,3.872488,1.000000
18,0.500000,3.698952,0.989583
19,0.500000,3.844830,0.989583
0,0.500000,3.413494,1.000000
0,0.500000,3.416399,1.000000
1,0.500000,3.396268,1.000000
2,0.500000,3.648122,1.000000
3,0.500000,3.889339,0.989583
4,0.500000,3.408539,1.000000
5,0.500000,4.625342,1.000000
6,0.500000,3.925502,0.989583
7,0.500000,3.033561,0.989583
8,0.500000,3.819170,0.989583
9,0.500000,4.497495,1.000000
10,0.500000,3.701839,1.000000
11,0.500000,4.369391,0.989583
12,0.500000,3.945474,1.000000
1 target_class parameter_mia_accuracy latent_distance_tell lookalike_accuracy
2 0 0.500000 3.219560 1.000000
3 1 0.500000 3.573733 1.000000
4 2 0.500000 3.924550 1.000000
5 3 0.500000 3.515182 1.000000
6 4 0.500000 3.369485 1.000000
7 5 0.500000 4.697085 1.000000
8 6 0.500000 4.185269 1.000000
9 7 0.500000 3.473583 1.000000
10 8 0.500000 4.518519 1.000000
11 9 0.500000 4.484542 1.000000
12 10 0.500000 3.353875 1.000000
13 11 0.500000 3.815037 0.989583
14 12 0.500000 3.493994 1.000000
15 13 0.500000 4.018041 1.000000
16 14 0.500000 4.059689 1.000000
17 15 0.500000 4.097189 1.000000
18 16 0.500000 3.287521 1.000000
19 17 0.500000 3.872488 1.000000
20 18 0.500000 3.698952 0.989583
21 19 0.500000 3.844830 0.989583
22 0 0.500000 3.413494 1.000000
23 0 0.500000 3.416399 1.000000
24 1 0.500000 3.396268 1.000000
25 2 0.500000 3.648122 1.000000
26 3 0.500000 3.889339 0.989583
27 4 0.500000 3.408539 1.000000
28 5 0.500000 4.625342 1.000000
29 6 0.500000 3.925502 0.989583
30 7 0.500000 3.033561 0.989583
31 8 0.500000 3.819170 0.989583
32 9 0.500000 4.497495 1.000000
33 10 0.500000 3.701839 1.000000
34 11 0.500000 4.369391 0.989583
35 12 0.500000 3.945474 1.000000