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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/CertifiedUnlearning/RESNET34/forget.csv
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@@ -364,3 +364,15 @@ 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
0.0125,1.0000,0.0125,0.0247,1.0000,0.0125,0.0247
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.4375,1.0000,0.4375,0.6087,1.0000,0.4375,0.6087
0.3875,1.0000,0.3875,0.5586,1.0000,0.3875,0.5586
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
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
367 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
368 0.4375 1.0000 0.4375 0.6087 1.0000 0.4375 0.6087
369 0.3875 1.0000 0.3875 0.5586 1.0000 0.3875 0.5586
370 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
371 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
372 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
373 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
374 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
375 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
376 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
377 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
378 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

12
reports/CertifiedUnlearning/RESNET34/forget_train.csv
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@@ -364,3 +364,15 @@ 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
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.5062,1.0000,0.5062,0.6722,1.0000,0.5062,0.6722
0.4750,1.0000,0.4750,0.6441,1.0000,0.4750,0.6441
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
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
367 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
368 0.5062 1.0000 0.5062 0.6722 1.0000 0.5062 0.6722
369 0.4750 1.0000 0.4750 0.6441 1.0000 0.4750 0.6441
370 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
371 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
372 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
373 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
374 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
375 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
376 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
377 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
378 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

12
reports/CertifiedUnlearning/RESNET34/retain.csv
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@@ -364,3 +364,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
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
0.1961,0.3286,0.1961,0.1473,0.3286,0.1961,0.1473
0.9474,0.9490,0.9474,0.9475,0.9490,0.9474,0.9475
0.9461,0.9485,0.9461,0.9462,0.9485,0.9461,0.9462
0.6309,0.8254,0.6309,0.6278,0.8254,0.6309,0.6278
0.9079,0.9297,0.9079,0.9121,0.9297,0.9079,0.9121
0.0526,0.0028,0.0526,0.0053,0.0028,0.0526,0.0053
0.8928,0.9239,0.8928,0.8992,0.9239,0.8928,0.8992
0.9316,0.9375,0.9316,0.9323,0.9375,0.9316,0.9323
0.8822,0.9078,0.8822,0.8844,0.9078,0.8822,0.8844
0.9053,0.9214,0.9053,0.9081,0.9214,0.9053,0.9081
0.0533,0.0343,0.0533,0.0077,0.0343,0.0533,0.0077
0.7171,0.8599,0.7171,0.7316,0.8599,0.7171,0.7316
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
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
367 0.1961 0.3286 0.1961 0.1473 0.3286 0.1961 0.1473
368 0.9474 0.9490 0.9474 0.9475 0.9490 0.9474 0.9475
369 0.9461 0.9485 0.9461 0.9462 0.9485 0.9461 0.9462
370 0.6309 0.8254 0.6309 0.6278 0.8254 0.6309 0.6278
371 0.9079 0.9297 0.9079 0.9121 0.9297 0.9079 0.9121
372 0.0526 0.0028 0.0526 0.0053 0.0028 0.0526 0.0053
373 0.8928 0.9239 0.8928 0.8992 0.9239 0.8928 0.8992
374 0.9316 0.9375 0.9316 0.9323 0.9375 0.9316 0.9323
375 0.8822 0.9078 0.8822 0.8844 0.9078 0.8822 0.8844
376 0.9053 0.9214 0.9053 0.9081 0.9214 0.9053 0.9081
377 0.0533 0.0343 0.0533 0.0077 0.0343 0.0533 0.0077
378 0.7171 0.8599 0.7171 0.7316 0.8599 0.7171 0.7316