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Tinsae
2026-07-08 00:25:07 +02:00
parent 026ca47800
commit eb8060fc05
37 changed files with 1649 additions and 66 deletions
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3
reports/CertifiedUnlearning/GOOGLENET/forget.csv Normal file
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accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1
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
2 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
3 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

3
reports/CertifiedUnlearning/GOOGLENET/forget_train.csv Normal file
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accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1
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
2 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
3 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

3
reports/CertifiedUnlearning/GOOGLENET/retain.csv Normal file
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accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1
0.9171,0.9251,0.9171,0.9180,0.9251,0.9171,0.9180
0.5539,0.8114,0.5539,0.5527,0.8114,0.5539,0.5527
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
2 0.9171 0.9251 0.9171 0.9180 0.9251 0.9171 0.9180
3 0.5539 0.8114 0.5539 0.5527 0.8114 0.5539 0.5527

3
reports/CertifiedUnlearning/GoogLeNet/time_metrics.txt Normal file
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execution_time_sec
310.029652
309.202731

20
reports/CertifiedUnlearning/RESNET34/forget.csv
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@@ -344,3 +344,23 @@ 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
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
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
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
0.0125,1.0000,0.0125,0.0247,1.0000,0.0125,0.0247
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
344 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
345 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
346 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
347 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
348 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
349 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
350 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
351 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
352 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
353 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
354 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
355 0.0375 1.0000 0.0375 0.0723 1.0000 0.0375 0.0723
356 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
357 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
358 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
359 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
360 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
361 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
362 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
363 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
364 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
365 0.0125 1.0000 0.0125 0.0247 1.0000 0.0125 0.0247
366 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

20
reports/CertifiedUnlearning/RESNET34/forget_train.csv
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@@ -344,3 +344,23 @@ 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
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
0.0031,1.0000,0.0031,0.0062,1.0000,0.0031,0.0062
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
0.0500,1.0000,0.0500,0.0952,1.0000,0.0500,0.0952
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
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
344 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
345 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
346 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
347 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
348 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
349 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
350 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
351 0.0031 1.0000 0.0031 0.0062 1.0000 0.0031 0.0062
352 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
353 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
354 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
355 0.0500 1.0000 0.0500 0.0952 1.0000 0.0500 0.0952
356 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
357 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
358 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
359 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
360 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
361 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
362 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
363 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
364 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
365 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
366 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

20
reports/CertifiedUnlearning/RESNET34/retain.csv
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@@ -344,3 +344,23 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.6434,0.8358,0.6434,0.6622,0.8358,0.6434,0.6622
0.7303,0.8317,0.7303,0.7303,0.8317,0.7303,0.7303
0.2895,0.4174,0.2895,0.2206,0.4174,0.2895,0.2206
0.8651,0.8977,0.8651,0.8664,0.8977,0.8651,0.8664
0.8349,0.8877,0.8349,0.8386,0.8877,0.8349,0.8386
0.9368,0.9409,0.9368,0.9373,0.9409,0.9368,0.9373
0.2474,0.6224,0.2474,0.2551,0.6224,0.2474,0.2551
0.9434,0.9479,0.9434,0.9441,0.9479,0.9434,0.9441
0.9283,0.9346,0.9283,0.9293,0.9346,0.9283,0.9293
0.9211,0.9285,0.9211,0.9221,0.9285,0.9211,0.9221
0.1316,0.5512,0.1316,0.1243,0.5512,0.1316,0.1243
0.9382,0.9418,0.9382,0.9390,0.9418,0.9382,0.9390
0.9191,0.9283,0.9191,0.9201,0.9283,0.9191,0.9201
0.4586,0.7992,0.4586,0.4860,0.7992,0.4586,0.4860
0.9086,0.9199,0.9086,0.9092,0.9199,0.9086,0.9092
0.9309,0.9360,0.9309,0.9315,0.9360,0.9309,0.9315
0.8500,0.9128,0.8500,0.8649,0.9128,0.8500,0.8649
0.9283,0.9364,0.9283,0.9293,0.9364,0.9283,0.9293
0.8921,0.9124,0.8921,0.8950,0.9124,0.8921,0.8950
0.8868,0.9181,0.8868,0.8927,0.9181,0.8868,0.8927
0.8730,0.9165,0.8730,0.8827,0.9165,0.8730,0.8827
0.9454,0.9470,0.9454,0.9454,0.9470,0.9454,0.9454
0.5987,0.7725,0.5987,0.5938,0.7725,0.5987,0.5938
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
344 0.6434 0.8358 0.6434 0.6622 0.8358 0.6434 0.6622
345 0.7303 0.8317 0.7303 0.7303 0.8317 0.7303 0.7303
346 0.2895 0.4174 0.2895 0.2206 0.4174 0.2895 0.2206
347 0.8651 0.8977 0.8651 0.8664 0.8977 0.8651 0.8664
348 0.8349 0.8877 0.8349 0.8386 0.8877 0.8349 0.8386
349 0.9368 0.9409 0.9368 0.9373 0.9409 0.9368 0.9373
350 0.2474 0.6224 0.2474 0.2551 0.6224 0.2474 0.2551
351 0.9434 0.9479 0.9434 0.9441 0.9479 0.9434 0.9441
352 0.9283 0.9346 0.9283 0.9293 0.9346 0.9283 0.9293
353 0.9211 0.9285 0.9211 0.9221 0.9285 0.9211 0.9221
354 0.1316 0.5512 0.1316 0.1243 0.5512 0.1316 0.1243
355 0.9382 0.9418 0.9382 0.9390 0.9418 0.9382 0.9390
356 0.9191 0.9283 0.9191 0.9201 0.9283 0.9191 0.9201
357 0.4586 0.7992 0.4586 0.4860 0.7992 0.4586 0.4860
358 0.9086 0.9199 0.9086 0.9092 0.9199 0.9086 0.9092
359 0.9309 0.9360 0.9309 0.9315 0.9360 0.9309 0.9315
360 0.8500 0.9128 0.8500 0.8649 0.9128 0.8500 0.8649
361 0.9283 0.9364 0.9283 0.9293 0.9364 0.9283 0.9293
362 0.8921 0.9124 0.8921 0.8950 0.9124 0.8921 0.8950
363 0.8868 0.9181 0.8868 0.8927 0.9181 0.8868 0.8927
364 0.8730 0.9165 0.8730 0.8827 0.9165 0.8730 0.8827
365 0.9454 0.9470 0.9454 0.9454 0.9470 0.9454 0.9454
366 0.5987 0.7725 0.5987 0.5938 0.7725 0.5987 0.5938

6
reports/CertifiedUnlearning/ResNet/time_metrics.txt
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@@ -358,3 +358,9 @@ execution_time_sec
395.473056
395.455440
395.554517
395.651279
400.544514
395.467196
395.553217
395.613947
395.703417

4
reports/CertifiedUnlearning/attack_values.csv Normal file
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target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
0,0.500000,7.219862,0.979167
1,0.500000,3.659238,0.958333
2,0.500000,6.939345,0.885417
1 target_class parameter_mia_accuracy latent_distance_tell lookalike_accuracy
2 0 0.500000 7.219862 0.979167
3 1 0.500000 3.659238 0.958333
4 2 0.500000 6.939345 0.885417

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reports/CertifiedUnlearning/attack_values_old.csv Normal file
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@@ -0,0 +1,101 @@
target_class,attack_mia_accuracy,latent_distance_tell
0,0.500000,8.166956
1,0.500000,6.160398
2,0.500000,6.704157
3,0.500000,7.097013
4,0.500000,7.059480
5,0.500000,5.941715
6,0.500000,7.376003
7,0.500000,6.876045
8,0.500000,7.853063
9,0.500000,7.215755
10,0.500000,6.611487
11,0.431250,6.596037
12,0.500000,7.509936
13,0.500000,6.233299
14,0.500000,9.069311
15,0.500000,7.752240
16,0.500000,7.227110
17,0.500000,5.331686
18,0.500000,8.771266
19,0.500000,5.970541
0,0.500000,8.333142
1,0.500000,4.603730
2,0.500000,6.403101
3,0.500000,7.975533
4,0.500000,6.620228
5,0.500000,8.796431
6,0.500000,9.078737
7,0.500000,6.821482
8,0.500000,9.727625
9,0.500000,9.074922
10,0.500000,6.036069
11,0.493750,7.097591
12,0.500000,5.960563
13,0.500000,6.122758
14,0.500000,8.211535
15,0.500000,7.850469
16,0.500000,6.859184
17,0.500000,5.088897
18,0.500000,9.236532
19,0.500000,7.642883
0,0.500000,8.106592
1,0.500000,6.134580
2,0.500000,6.941654
3,0.500000,7.773781
4,0.500000,7.363125
5,0.500000,6.496724
6,0.500000,7.648515
7,0.500000,8.689814
8,0.500000,8.578580
9,0.500000,9.119745
10,0.500000,5.984212
11,0.468750,6.359155
12,0.500000,7.997709
13,0.500000,6.927951
14,0.500000,8.872922
15,0.500000,7.429983
16,0.500000,6.928881
17,0.500000,5.071527
18,0.500000,8.475766
19,0.500000,6.096026
0,0.500000,7.570661
1,0.500000,3.468966
2,0.500000,5.726584
3,0.500000,7.681168
4,0.500000,7.824241
5,0.500000,9.169927
6,0.500000,7.778905
7,0.500000,8.138535
8,0.500000,9.735314
9,0.500000,7.250852
10,0.500000,6.852473
11,0.462500,7.474597
12,0.500000,5.709781
13,0.500000,7.201421
14,0.500000,9.513277
15,0.500000,7.965966
16,0.500000,6.824328
17,0.500000,5.539176
18,0.500000,9.225863
19,0.500000,7.838114
0,0.500000,7.209781
1,0.500000,3.245398
2,0.500000,6.559930
3,0.500000,8.221349
4,0.500000,7.320590
5,0.500000,8.885569
6,0.500000,7.456804
7,0.500000,7.722786
8,0.500000,8.868426
9,0.500000,6.132468
10,0.500000,7.281767
11,0.481250,7.443795
12,0.500000,7.379603
13,0.500000,6.809259
14,0.500000,8.274336
15,0.500000,8.232855
16,0.500000,7.061528
17,0.500000,6.004038
18,0.500000,8.139433
19,0.500000,7.296746
1 target_class attack_mia_accuracy latent_distance_tell
2 0 0.500000 8.166956
3 1 0.500000 6.160398
4 2 0.500000 6.704157
5 3 0.500000 7.097013
6 4 0.500000 7.059480
7 5 0.500000 5.941715
8 6 0.500000 7.376003
9 7 0.500000 6.876045
10 8 0.500000 7.853063
11 9 0.500000 7.215755
12 10 0.500000 6.611487
13 11 0.431250 6.596037
14 12 0.500000 7.509936
15 13 0.500000 6.233299
16 14 0.500000 9.069311
17 15 0.500000 7.752240
18 16 0.500000 7.227110
19 17 0.500000 5.331686
20 18 0.500000 8.771266
21 19 0.500000 5.970541
22 0 0.500000 8.333142
23 1 0.500000 4.603730
24 2 0.500000 6.403101
25 3 0.500000 7.975533
26 4 0.500000 6.620228
27 5 0.500000 8.796431
28 6 0.500000 9.078737
29 7 0.500000 6.821482
30 8 0.500000 9.727625
31 9 0.500000 9.074922
32 10 0.500000 6.036069
33 11 0.493750 7.097591
34 12 0.500000 5.960563
35 13 0.500000 6.122758
36 14 0.500000 8.211535
37 15 0.500000 7.850469
38 16 0.500000 6.859184
39 17 0.500000 5.088897
40 18 0.500000 9.236532
41 19 0.500000 7.642883
42 0 0.500000 8.106592
43 1 0.500000 6.134580
44 2 0.500000 6.941654
45 3 0.500000 7.773781
46 4 0.500000 7.363125
47 5 0.500000 6.496724
48 6 0.500000 7.648515
49 7 0.500000 8.689814
50 8 0.500000 8.578580
51 9 0.500000 9.119745
52 10 0.500000 5.984212
53 11 0.468750 6.359155
54 12 0.500000 7.997709
55 13 0.500000 6.927951
56 14 0.500000 8.872922
57 15 0.500000 7.429983
58 16 0.500000 6.928881
59 17 0.500000 5.071527
60 18 0.500000 8.475766
61 19 0.500000 6.096026
62 0 0.500000 7.570661
63 1 0.500000 3.468966
64 2 0.500000 5.726584
65 3 0.500000 7.681168
66 4 0.500000 7.824241
67 5 0.500000 9.169927
68 6 0.500000 7.778905
69 7 0.500000 8.138535
70 8 0.500000 9.735314
71 9 0.500000 7.250852
72 10 0.500000 6.852473
73 11 0.462500 7.474597
74 12 0.500000 5.709781
75 13 0.500000 7.201421
76 14 0.500000 9.513277
77 15 0.500000 7.965966
78 16 0.500000 6.824328
79 17 0.500000 5.539176
80 18 0.500000 9.225863
81 19 0.500000 7.838114
82 0 0.500000 7.209781
83 1 0.500000 3.245398
84 2 0.500000 6.559930
85 3 0.500000 8.221349
86 4 0.500000 7.320590
87 5 0.500000 8.885569
88 6 0.500000 7.456804
89 7 0.500000 7.722786
90 8 0.500000 8.868426
91 9 0.500000 6.132468
92 10 0.500000 7.281767
93 11 0.481250 7.443795
94 12 0.500000 7.379603
95 13 0.500000 6.809259
96 14 0.500000 8.274336
97 15 0.500000 8.232855
98 16 0.500000 7.061528
99 17 0.500000 6.004038
100 18 0.500000 8.139433
101 19 0.500000 7.296746