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test_config.txt
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4280 lines (4098 loc) · 177 KB
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========Testing Regularization =========
======== cifar10 =========
======== resnet =========
0
0.1
0.3
1
3
10
30
100
∞
======== densenet =========
0
0.1
0.3
1
3
10
30
100
∞
======== svhn =========
======== resnet =========
0
0.1
0.3
1
3
10
30
100
∞
======== densenet =========
0
0.1
0.3
1
3
10
30
100
∞
======== cifar100 =========
======== resnet =========
0
0.1
0.3
1
3
10
30
100
∞
======== densenet =========
0
0.1
0.3
1
3
10
30
100
∞
========Testing Features =========
======== cifar10 =========
======== resnet =========
Min & Max
Creating Calibration Set
Creating Augmented Set
Creating Mixed Up Set
Creating Noisy Set
Creating Shifted Set
Creating Blurry Set
Creating Shifted Set
Fitting Logistic Regression
mean_test_score ... params
0 0.879615 ... {'lr__C': 1e-08}
1 0.879868 ... {'lr__C': 3.162277660168379e-08}
2 0.880666 ... {'lr__C': 1e-07}
3 0.882914 ... {'lr__C': 3.162277660168379e-07}
4 0.888167 ... {'lr__C': 1e-06}
5 0.895402 ... {'lr__C': 3.162277660168379e-06}
6 0.900094 ... {'lr__C': 1e-05}
7 0.900195 ... {'lr__C': 3.1622776601683795e-05}
8 0.893321 ... {'lr__C': 0.0001}
9 0.877059 ... {'lr__C': 0.00031622776601683794}
10 0.859284 ... {'lr__C': 0.001}
11 0.845344 ... {'lr__C': 0.0031622776601683794}
12 0.835988 ... {'lr__C': 0.01}
13 0.830919 ... {'lr__C': 0.03162277660168379}
14 0.828692 ... {'lr__C': 0.1}
15 0.827879 ... {'lr__C': 0.31622776601683794}
16 0.827593 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.024760
Min_out+ 0.058456
Min_relu_32+ 0.014673
Max_relu_32+ 0.017351
Min_relu_0+ 0.016812
...
Max_relu_29- 0.048585
Min_relu_30- 0.056098
Max_relu_30- 0.018821
Min_relu_31- -0.031255
Max_relu_31- 0.038651
Length: 136, dtype: float64
Min
Fitting Logistic Regression
mean_test_score ... params
0 0.893056 ... {'lr__C': 1e-08}
1 0.893117 ... {'lr__C': 3.162277660168379e-08}
2 0.893322 ... {'lr__C': 1e-07}
3 0.893931 ... {'lr__C': 3.162277660168379e-07}
4 0.895519 ... {'lr__C': 1e-06}
5 0.898714 ... {'lr__C': 3.162277660168379e-06}
6 0.902211 ... {'lr__C': 1e-05}
7 0.903500 ... {'lr__C': 3.1622776601683795e-05}
8 0.900103 ... {'lr__C': 0.0001}
9 0.888089 ... {'lr__C': 0.00031622776601683794}
10 0.871229 ... {'lr__C': 0.001}
11 0.857376 ... {'lr__C': 0.0031622776601683794}
12 0.848316 ... {'lr__C': 0.01}
13 0.843451 ... {'lr__C': 0.03162277660168379}
14 0.841354 ... {'lr__C': 0.1}
15 0.840573 ... {'lr__C': 0.31622776601683794}
16 0.840332 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.034410
Min_out+ 0.072311
Min_relu_32+ 0.024996
Min_relu_0+ 0.026495
Min_relu_1+ 0.027862
...
Min_relu_27- 0.027891
Min_relu_28- 0.074198
Min_relu_29- 0.035725
Min_relu_30- 0.077423
Min_relu_31- -0.040803
Length: 70, dtype: float64
Max
Fitting Logistic Regression
mean_test_score ... params
0 0.865933 ... {'lr__C': 1e-08}
1 0.866095 ... {'lr__C': 3.162277660168379e-08}
2 0.866610 ... {'lr__C': 1e-07}
3 0.868173 ... {'lr__C': 3.162277660168379e-07}
4 0.872539 ... {'lr__C': 1e-06}
5 0.881940 ... {'lr__C': 3.162277660168379e-06}
6 0.892586 ... {'lr__C': 1e-05}
7 0.897054 ... {'lr__C': 3.1622776601683795e-05}
8 0.894718 ... {'lr__C': 0.0001}
9 0.885715 ... {'lr__C': 0.00031622776601683794}
10 0.873460 ... {'lr__C': 0.001}
11 0.862716 ... {'lr__C': 0.0031622776601683794}
12 0.855110 ... {'lr__C': 0.01}
13 0.851086 ... {'lr__C': 0.03162277660168379}
14 0.849255 ... {'lr__C': 0.1}
15 0.848590 ... {'lr__C': 0.31622776601683794}
16 0.848341 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.034312
Min_out+ 0.075768
Max_relu_32+ 0.029429
Max_relu_0+ 0.030357
Max_relu_1+ 0.031554
...
Max_relu_27- 0.076165
Max_relu_28- 0.078365
Max_relu_29- 0.069973
Max_relu_30- 0.032114
Max_relu_31- 0.049387
Length: 70, dtype: float64
Positivity
Fitting Logistic Regression
mean_test_score ... params
0 0.866958 ... {'lr__C': 1e-08}
1 0.867001 ... {'lr__C': 3.162277660168379e-08}
2 0.867141 ... {'lr__C': 1e-07}
3 0.867574 ... {'lr__C': 3.162277660168379e-07}
4 0.868806 ... {'lr__C': 1e-06}
5 0.871837 ... {'lr__C': 3.162277660168379e-06}
6 0.876384 ... {'lr__C': 1e-05}
7 0.877711 ... {'lr__C': 3.1622776601683795e-05}
8 0.871218 ... {'lr__C': 0.0001}
9 0.858872 ... {'lr__C': 0.00031622776601683794}
10 0.845053 ... {'lr__C': 0.001}
11 0.833039 ... {'lr__C': 0.0031622776601683794}
12 0.824278 ... {'lr__C': 0.01}
13 0.818739 ... {'lr__C': 0.03162277660168379}
14 0.815959 ... {'lr__C': 0.1}
15 0.814831 ... {'lr__C': 0.31622776601683794}
16 0.814472 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.035911
Min_out+ 0.076429
Positivity_relu_32+ 0.019995
Positivity_relu_0+ 0.005334
Positivity_relu_1+ 0.022054
...
Positivity_relu_27- -0.012820
Positivity_relu_28- -0.045878
Positivity_relu_29- -0.046604
Positivity_relu_30- -0.052245
Positivity_relu_31- -0.043951
Length: 70, dtype: float64
Sum
Fitting Logistic Regression
mean_test_score ... params
0 0.880324 ... {'lr__C': 1e-08}
1 0.880350 ... {'lr__C': 3.162277660168379e-08}
2 0.880423 ... {'lr__C': 1e-07}
3 0.880646 ... {'lr__C': 3.162277660168379e-07}
4 0.881287 ... {'lr__C': 1e-06}
5 0.882811 ... {'lr__C': 3.162277660168379e-06}
6 0.884694 ... {'lr__C': 1e-05}
7 0.882927 ... {'lr__C': 3.1622776601683795e-05}
8 0.872137 ... {'lr__C': 0.0001}
9 0.854693 ... {'lr__C': 0.00031622776601683794}
10 0.837520 ... {'lr__C': 0.001}
11 0.823857 ... {'lr__C': 0.0031622776601683794}
12 0.813960 ... {'lr__C': 0.01}
13 0.807335 ... {'lr__C': 0.03162277660168379}
14 0.803401 ... {'lr__C': 0.1}
15 0.801555 ... {'lr__C': 0.31622776601683794}
16 0.801135 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.019851
Min_out+ 0.039176
Sum_relu_32+ 0.010243
Sum_relu_0+ 0.006468
Sum_relu_1+ 0.007944
...
Sum_relu_27- 0.031197
Sum_relu_28- -0.021758
Sum_relu_29- 0.040657
Sum_relu_30- -0.022673
Sum_relu_31- -0.014352
Length: 70, dtype: float64
L1
Fitting Logistic Regression
mean_test_score ... params
0 0.867516 ... {'lr__C': 1e-08}
1 0.867625 ... {'lr__C': 3.162277660168379e-08}
2 0.867984 ... {'lr__C': 1e-07}
3 0.869072 ... {'lr__C': 3.162277660168379e-07}
4 0.872050 ... {'lr__C': 1e-06}
5 0.878454 ... {'lr__C': 3.162277660168379e-06}
6 0.886103 ... {'lr__C': 1e-05}
7 0.889193 ... {'lr__C': 3.1622776601683795e-05}
8 0.882668 ... {'lr__C': 0.0001}
9 0.866538 ... {'lr__C': 0.00031622776601683794}
10 0.848840 ... {'lr__C': 0.001}
11 0.833714 ... {'lr__C': 0.0031622776601683794}
12 0.821639 ... {'lr__C': 0.01}
13 0.812919 ... {'lr__C': 0.03162277660168379}
14 0.806687 ... {'lr__C': 0.1}
15 0.802183 ... {'lr__C': 0.31622776601683794}
16 0.799089 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.031456
Min_out+ 0.076343
L1-norm_relu_32+ 0.022345
L1-norm_relu_0+ 0.027135
L1-norm_relu_1+ 0.031708
...
L1-norm_relu_27- 0.056355
L1-norm_relu_28- 0.089939
L1-norm_relu_29- 0.075189
L1-norm_relu_30- 0.090079
L1-norm_relu_31- -0.037781
Length: 70, dtype: float64
L2
Fitting Logistic Regression
mean_test_score ... params
0 0.874342 ... {'lr__C': 1e-08}
1 0.874445 ... {'lr__C': 3.162277660168379e-08}
2 0.874760 ... {'lr__C': 1e-07}
3 0.875700 ... {'lr__C': 3.162277660168379e-07}
4 0.878286 ... {'lr__C': 1e-06}
5 0.883561 ... {'lr__C': 3.162277660168379e-06}
6 0.889447 ... {'lr__C': 1e-05}
7 0.891215 ... {'lr__C': 3.1622776601683795e-05}
8 0.883872 ... {'lr__C': 0.0001}
9 0.867251 ... {'lr__C': 0.00031622776601683794}
10 0.849588 ... {'lr__C': 0.001}
11 0.834850 ... {'lr__C': 0.0031622776601683794}
12 0.822349 ... {'lr__C': 0.01}
13 0.812598 ... {'lr__C': 0.03162277660168379}
14 0.805721 ... {'lr__C': 0.1}
15 0.801066 ... {'lr__C': 0.31622776601683794}
16 0.798237 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.027987
Min_out+ 0.076727
L2-norm_relu_32+ 0.021073
L2-norm_relu_0+ 0.027088
L2-norm_relu_1+ 0.029704
...
L2-norm_relu_27- 0.066865
L2-norm_relu_28- 0.085302
L2-norm_relu_29- 0.084095
L2-norm_relu_30- 0.085469
L2-norm_relu_31- 0.052389
Length: 70, dtype: float64
L3
Fitting Logistic Regression
mean_test_score ... params
0 0.876535 ... {'lr__C': 1e-08}
1 0.876645 ... {'lr__C': 3.162277660168379e-08}
2 0.876980 ... {'lr__C': 1e-07}
3 0.877968 ... {'lr__C': 3.162277660168379e-07}
4 0.880627 ... {'lr__C': 1e-06}
5 0.885900 ... {'lr__C': 3.162277660168379e-06}
6 0.891639 ... {'lr__C': 1e-05}
7 0.893073 ... {'lr__C': 3.1622776601683795e-05}
8 0.885606 ... {'lr__C': 0.0001}
9 0.868857 ... {'lr__C': 0.00031622776601683794}
10 0.850923 ... {'lr__C': 0.001}
11 0.836148 ... {'lr__C': 0.0031622776601683794}
12 0.824189 ... {'lr__C': 0.01}
13 0.814938 ... {'lr__C': 0.03162277660168379}
14 0.808464 ... {'lr__C': 0.1}
15 0.804301 ... {'lr__C': 0.31622776601683794}
16 0.802039 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.027517
Min_out+ 0.074607
L3-norm_relu_32+ 0.021895
L3-norm_relu_0+ 0.027770
L3-norm_relu_1+ 0.029093
...
L3-norm_relu_27- 0.073037
L3-norm_relu_28- 0.082947
L3-norm_relu_29- 0.084849
L3-norm_relu_30- 0.082737
L3-norm_relu_31- 0.062265
Length: 70, dtype: float64
Split L1
Fitting Logistic Regression
mean_test_score ... params
0 0.855523 ... {'lr__C': 1e-08}
1 0.855699 ... {'lr__C': 3.162277660168379e-08}
2 0.856232 ... {'lr__C': 1e-07}
3 0.857848 ... {'lr__C': 3.162277660168379e-07}
4 0.862023 ... {'lr__C': 1e-06}
5 0.869577 ... {'lr__C': 3.162277660168379e-06}
6 0.877208 ... {'lr__C': 1e-05}
7 0.877875 ... {'lr__C': 3.1622776601683795e-05}
8 0.865811 ... {'lr__C': 0.0001}
9 0.847343 ... {'lr__C': 0.00031622776601683794}
10 0.829815 ... {'lr__C': 0.001}
11 0.814825 ... {'lr__C': 0.0031622776601683794}
12 0.803338 ... {'lr__C': 0.01}
13 0.795629 ... {'lr__C': 0.03162277660168379}
14 0.790465 ... {'lr__C': 0.1}
15 0.786961 ... {'lr__C': 0.31622776601683794}
16 0.784580 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.025626
Min_out+ 0.064377
NegLpNorm_relu_32+ 0.012787
PosLpNorm_relu_32+ 0.016172
NegLpNorm_relu_0+ 0.015829
...
PosLpNorm_relu_29- 0.057851
NegLpNorm_relu_30- 0.072280
PosLpNorm_relu_30- -0.031167
NegLpNorm_relu_31- -0.006212
PosLpNorm_relu_31- -0.037574
Length: 136, dtype: float64
Split L2
Fitting Logistic Regression
mean_test_score ... params
0 0.865454 ... {'lr__C': 1e-08}
1 0.865711 ... {'lr__C': 3.162277660168379e-08}
2 0.866498 ... {'lr__C': 1e-07}
3 0.868824 ... {'lr__C': 3.162277660168379e-07}
4 0.874366 ... {'lr__C': 1e-06}
5 0.882855 ... {'lr__C': 3.162277660168379e-06}
6 0.889357 ... {'lr__C': 1e-05}
7 0.889387 ... {'lr__C': 3.1622776601683795e-05}
8 0.877998 ... {'lr__C': 0.0001}
9 0.858232 ... {'lr__C': 0.00031622776601683794}
10 0.839373 ... {'lr__C': 0.001}
11 0.823952 ... {'lr__C': 0.0031622776601683794}
12 0.811312 ... {'lr__C': 0.01}
13 0.801750 ... {'lr__C': 0.03162277660168379}
14 0.794715 ... {'lr__C': 0.1}
15 0.789678 ... {'lr__C': 0.31622776601683794}
16 0.786103 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.020313
Min_out+ 0.061002
NegLpNorm_relu_32+ 0.012577
PosLpNorm_relu_32+ 0.014557
NegLpNorm_relu_0+ 0.015824
...
PosLpNorm_relu_29- 0.066416
NegLpNorm_relu_30- 0.066070
PosLpNorm_relu_30- 0.003553
NegLpNorm_relu_31- -0.024895
PosLpNorm_relu_31- 0.050595
Length: 136, dtype: float64
Split L3
Fitting Logistic Regression
mean_test_score ... params
0 0.871531 ... {'lr__C': 1e-08}
1 0.871793 ... {'lr__C': 3.162277660168379e-08}
2 0.872616 ... {'lr__C': 1e-07}
3 0.874992 ... {'lr__C': 3.162277660168379e-07}
4 0.880625 ... {'lr__C': 1e-06}
5 0.888721 ... {'lr__C': 3.162277660168379e-06}
6 0.894202 ... {'lr__C': 1e-05}
7 0.893388 ... {'lr__C': 3.1622776601683795e-05}
8 0.881978 ... {'lr__C': 0.0001}
9 0.862031 ... {'lr__C': 0.00031622776601683794}
10 0.843010 ... {'lr__C': 0.001}
11 0.827490 ... {'lr__C': 0.0031622776601683794}
12 0.814854 ... {'lr__C': 0.01}
13 0.805196 ... {'lr__C': 0.03162277660168379}
14 0.798634 ... {'lr__C': 0.1}
15 0.794498 ... {'lr__C': 0.31622776601683794}
16 0.792179 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.012676
Min_out+ 0.030524
NegLpNorm_relu_32+ 0.009690
PosLpNorm_relu_32+ 0.011452
NegLpNorm_relu_0+ 0.011787
...
PosLpNorm_relu_29- 0.036199
NegLpNorm_relu_30- 0.035687
PosLpNorm_relu_30- 0.014494
NegLpNorm_relu_31- -0.016028
PosLpNorm_relu_31- 0.029026
Length: 136, dtype: float64
======== densenet =========
Min & Max
Fitting Logistic Regression
mean_test_score ... params
0 0.806712 ... {'lr__C': 1e-08}
1 0.807636 ... {'lr__C': 3.162277660168379e-08}
2 0.810466 ... {'lr__C': 1e-07}
3 0.818953 ... {'lr__C': 3.162277660168379e-07}
4 0.839692 ... {'lr__C': 1e-06}
5 0.864585 ... {'lr__C': 3.162277660168379e-06}
6 0.874735 ... {'lr__C': 1e-05}
7 0.878816 ... {'lr__C': 3.1622776601683795e-05}
8 0.880273 ... {'lr__C': 0.0001}
9 0.869192 ... {'lr__C': 0.00031622776601683794}
10 0.847309 ... {'lr__C': 0.001}
11 0.828623 ... {'lr__C': 0.0031622776601683794}
12 0.816455 ... {'lr__C': 0.01}
13 0.810090 ... {'lr__C': 0.03162277660168379}
14 0.807091 ... {'lr__C': 0.1}
15 0.805795 ... {'lr__C': 0.31622776601683794}
16 0.805299 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.091725
Min_out+ 0.013650
Min_relu_0+ 0.012550
Max_relu_0+ 0.016409
Min_relu_1+ 0.022546
...
Max_relu_48- 0.010274
Min_relu_49- 0.035911
Max_relu_49- 0.057128
Min_relu_50- 0.053466
Max_relu_50- 0.045103
Length: 208, dtype: float64
Min
Fitting Logistic Regression
mean_test_score ... params
0 0.794068 ... {'lr__C': 1e-08}
1 0.794553 ... {'lr__C': 3.162277660168379e-08}
2 0.796087 ... {'lr__C': 1e-07}
3 0.800855 ... {'lr__C': 3.162277660168379e-07}
4 0.814686 ... {'lr__C': 1e-06}
5 0.844063 ... {'lr__C': 3.162277660168379e-06}
6 0.866791 ... {'lr__C': 1e-05}
7 0.874013 ... {'lr__C': 3.1622776601683795e-05}
8 0.876340 ... {'lr__C': 0.0001}
9 0.870914 ... {'lr__C': 0.00031622776601683794}
10 0.853507 ... {'lr__C': 0.001}
11 0.835304 ... {'lr__C': 0.0031622776601683794}
12 0.823000 ... {'lr__C': 0.01}
13 0.816623 ... {'lr__C': 0.03162277660168379}
14 0.813935 ... {'lr__C': 0.1}
15 0.812943 ... {'lr__C': 0.31622776601683794}
16 0.812606 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.108425
Min_out+ 0.019805
Min_relu_0+ 0.026679
Min_relu_1+ 0.041415
Min_relu_2+ 0.026114
...
Min_relu_46- 0.051618
Min_relu_47- 0.029238
Min_relu_48- 0.034734
Min_relu_49- 0.055216
Min_relu_50- 0.077053
Length: 106, dtype: float64
Max
Fitting Logistic Regression
mean_test_score ... params
0 0.827444 ... {'lr__C': 1e-08}
1 0.827840 ... {'lr__C': 3.162277660168379e-08}
2 0.829094 ... {'lr__C': 1e-07}
3 0.832879 ... {'lr__C': 3.162277660168379e-07}
4 0.843378 ... {'lr__C': 1e-06}
5 0.863144 ... {'lr__C': 3.162277660168379e-06}
6 0.878983 ... {'lr__C': 1e-05}
7 0.885858 ... {'lr__C': 3.1622776601683795e-05}
8 0.889676 ... {'lr__C': 0.0001}
9 0.886450 ... {'lr__C': 0.00031622776601683794}
10 0.870370 ... {'lr__C': 0.001}
11 0.853215 ... {'lr__C': 0.0031622776601683794}
12 0.841640 ... {'lr__C': 0.01}
13 0.835573 ... {'lr__C': 0.03162277660168379}
14 0.833016 ... {'lr__C': 0.1}
15 0.832083 ... {'lr__C': 0.31622776601683794}
16 0.831771 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.100693
Min_out+ 0.013047
Max_relu_0+ 0.031319
Max_relu_1+ 0.036570
Max_relu_2+ 0.031978
...
Max_relu_46- 0.073926
Max_relu_47- 0.076486
Max_relu_48- 0.016253
Max_relu_49- 0.071083
Max_relu_50- 0.053891
Length: 106, dtype: float64
Positivity
Fitting Logistic Regression
mean_test_score ... params
0 0.760242 ... {'lr__C': 1e-08}
1 0.760360 ... {'lr__C': 3.162277660168379e-08}
2 0.760731 ... {'lr__C': 1e-07}
3 0.761858 ... {'lr__C': 3.162277660168379e-07}
4 0.765134 ... {'lr__C': 1e-06}
5 0.773516 ... {'lr__C': 3.162277660168379e-06}
6 0.789219 ... {'lr__C': 1e-05}
7 0.810008 ... {'lr__C': 3.1622776601683795e-05}
8 0.828017 ... {'lr__C': 0.0001}
9 0.830289 ... {'lr__C': 0.00031622776601683794}
10 0.819315 ... {'lr__C': 0.001}
11 0.805830 ... {'lr__C': 0.0031622776601683794}
12 0.795270 ... {'lr__C': 0.01}
13 0.788895 ... {'lr__C': 0.03162277660168379}
14 0.785741 ... {'lr__C': 0.1}
15 0.784474 ... {'lr__C': 0.31622776601683794}
16 0.784033 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.187734
Min_out+ 0.030307
Positivity_relu_0+ 0.031746
Positivity_relu_1+ 0.005708
Positivity_relu_2+ -0.002902
...
Positivity_relu_46- -0.047425
Positivity_relu_47- -0.024160
Positivity_relu_48- -0.025864
Positivity_relu_49- -0.058572
Positivity_relu_50- 0.006720
Length: 106, dtype: float64
Sum
Fitting Logistic Regression
mean_test_score ... params
0 0.762635 ... {'lr__C': 1e-08}
1 0.762847 ... {'lr__C': 3.162277660168379e-08}
2 0.763515 ... {'lr__C': 1e-07}
3 0.765491 ... {'lr__C': 3.162277660168379e-07}
4 0.770777 ... {'lr__C': 1e-06}
5 0.781049 ... {'lr__C': 3.162277660168379e-06}
6 0.793092 ... {'lr__C': 1e-05}
7 0.802455 ... {'lr__C': 3.1622776601683795e-05}
8 0.807846 ... {'lr__C': 0.0001}
9 0.807153 ... {'lr__C': 0.00031622776601683794}
10 0.801332 ... {'lr__C': 0.001}
11 0.793105 ... {'lr__C': 0.0031622776601683794}
12 0.786131 ... {'lr__C': 0.01}
13 0.781144 ... {'lr__C': 0.03162277660168379}
14 0.777591 ... {'lr__C': 0.1}
15 0.775326 ... {'lr__C': 0.31622776601683794}
16 0.774208 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.113400
Min_out+ 0.023966
Sum_relu_0+ 0.015941
Sum_relu_1+ 0.017972
Sum_relu_2+ 0.003058
...
Sum_relu_46- -0.072510
Sum_relu_47- -0.004556
Sum_relu_48- 0.004421
Sum_relu_49- -0.018730
Sum_relu_50- 0.047060
Length: 106, dtype: float64
L1
Fitting Logistic Regression
mean_test_score ... params
0 0.760369 ... {'lr__C': 1e-08}
1 0.760976 ... {'lr__C': 3.162277660168379e-08}
2 0.762847 ... {'lr__C': 1e-07}
3 0.768404 ... {'lr__C': 3.162277660168379e-07}
4 0.783221 ... {'lr__C': 1e-06}
5 0.806473 ... {'lr__C': 3.162277660168379e-06}
6 0.825100 ... {'lr__C': 1e-05}
7 0.833096 ... {'lr__C': 3.1622776601683795e-05}
8 0.830836 ... {'lr__C': 0.0001}
9 0.822587 ... {'lr__C': 0.00031622776601683794}
10 0.813808 ... {'lr__C': 0.001}
11 0.802842 ... {'lr__C': 0.0031622776601683794}
12 0.791403 ... {'lr__C': 0.01}
13 0.781086 ... {'lr__C': 0.03162277660168379}
14 0.773486 ... {'lr__C': 0.1}
15 0.768707 ... {'lr__C': 0.31622776601683794}
16 0.766052 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.056475
Min_out+ 0.012369
L1-norm_relu_0+ 0.017795
L1-norm_relu_1+ 0.020985
L1-norm_relu_2+ 0.013064
...
L1-norm_relu_46- 0.029847
L1-norm_relu_47- 0.036742
L1-norm_relu_48- 0.012426
L1-norm_relu_49- 0.020808
L1-norm_relu_50- 0.048515
Length: 106, dtype: float64
L2
Fitting Logistic Regression
mean_test_score ... params
0 0.768624 ... {'lr__C': 1e-08}
1 0.769243 ... {'lr__C': 3.162277660168379e-08}
2 0.771176 ... {'lr__C': 1e-07}
3 0.776951 ... {'lr__C': 3.162277660168379e-07}
4 0.792004 ... {'lr__C': 1e-06}
5 0.815986 ... {'lr__C': 3.162277660168379e-06}
6 0.834488 ... {'lr__C': 1e-05}
7 0.842287 ... {'lr__C': 3.1622776601683795e-05}
8 0.839687 ... {'lr__C': 0.0001}
9 0.829460 ... {'lr__C': 0.00031622776601683794}
10 0.818181 ... {'lr__C': 0.001}
11 0.805158 ... {'lr__C': 0.0031622776601683794}
12 0.792237 ... {'lr__C': 0.01}
13 0.781349 ... {'lr__C': 0.03162277660168379}
14 0.773721 ... {'lr__C': 0.1}
15 0.769192 ... {'lr__C': 0.31622776601683794}
16 0.766905 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.054713
Min_out+ 0.012521
L2-norm_relu_0+ 0.019475
L2-norm_relu_1+ 0.021373
L2-norm_relu_2+ 0.014275
...
L2-norm_relu_46- 0.030849
L2-norm_relu_47- 0.035094
L2-norm_relu_48- 0.012872
L2-norm_relu_49- 0.022268
L2-norm_relu_50- 0.059973
Length: 106, dtype: float64
L3
Fitting Logistic Regression
mean_test_score ... params
0 0.774427 ... {'lr__C': 1e-08}
1 0.775052 ... {'lr__C': 3.162277660168379e-08}
2 0.776989 ... {'lr__C': 1e-07}
3 0.782831 ... {'lr__C': 3.162277660168379e-07}
4 0.798294 ... {'lr__C': 1e-06}
5 0.823406 ... {'lr__C': 3.162277660168379e-06}
6 0.841950 ... {'lr__C': 1e-05}
7 0.849277 ... {'lr__C': 3.1622776601683795e-05}
8 0.846375 ... {'lr__C': 0.0001}
9 0.834813 ... {'lr__C': 0.00031622776601683794}
10 0.821812 ... {'lr__C': 0.001}
11 0.807862 ... {'lr__C': 0.0031622776601683794}
12 0.794546 ... {'lr__C': 0.01}
13 0.783711 ... {'lr__C': 0.03162277660168379}
14 0.776295 ... {'lr__C': 0.1}
15 0.772171 ... {'lr__C': 0.31622776601683794}
16 0.770288 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.054594
Min_out+ 0.011989
L3-norm_relu_0+ 0.021135
L3-norm_relu_1+ 0.021804
L3-norm_relu_2+ 0.015045
...
L3-norm_relu_46- 0.032244
L3-norm_relu_47- 0.033705
L3-norm_relu_48- 0.013806
L3-norm_relu_49- 0.023510
L3-norm_relu_50- 0.060743
Length: 106, dtype: float64
Split L1
Fitting Logistic Regression
mean_test_score ... params
0 0.766348 ... {'lr__C': 1e-08}
1 0.767233 ... {'lr__C': 3.162277660168379e-08}
2 0.769890 ... {'lr__C': 1e-07}
3 0.776981 ... {'lr__C': 3.162277660168379e-07}
4 0.791670 ... {'lr__C': 1e-06}
5 0.808985 ... {'lr__C': 3.162277660168379e-06}
6 0.820198 ... {'lr__C': 1e-05}
7 0.826186 ... {'lr__C': 3.1622776601683795e-05}
8 0.822962 ... {'lr__C': 0.0001}
9 0.813483 ... {'lr__C': 0.00031622776601683794}
10 0.802067 ... {'lr__C': 0.001}
11 0.789042 ... {'lr__C': 0.0031622776601683794}
12 0.776561 ... {'lr__C': 0.01}
13 0.767073 ... {'lr__C': 0.03162277660168379}
14 0.760973 ... {'lr__C': 0.1}
15 0.757287 ... {'lr__C': 0.31622776601683794}
16 0.754927 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.049502
Min_out+ 0.009985
NegLpNorm_relu_0+ 0.009879
PosLpNorm_relu_0+ 0.012456
NegLpNorm_relu_1+ 0.012439
...
PosLpNorm_relu_48- 0.014977
NegLpNorm_relu_49- 0.017869
PosLpNorm_relu_49- 0.009782
NegLpNorm_relu_50- 0.049057
PosLpNorm_relu_50- 0.024516
Length: 208, dtype: float64
Split L2
Fitting Logistic Regression
mean_test_score ... params
0 0.778942 ... {'lr__C': 1e-08}
1 0.780040 ... {'lr__C': 3.162277660168379e-08}
2 0.783395 ... {'lr__C': 1e-07}
3 0.792840 ... {'lr__C': 3.162277660168379e-07}
4 0.811260 ... {'lr__C': 1e-06}
5 0.831167 ... {'lr__C': 3.162277660168379e-06}
6 0.841426 ... {'lr__C': 1e-05}
7 0.844031 ... {'lr__C': 3.1622776601683795e-05}
8 0.835027 ... {'lr__C': 0.0001}
9 0.820255 ... {'lr__C': 0.00031622776601683794}
10 0.807635 ... {'lr__C': 0.001}
11 0.795420 ... {'lr__C': 0.0031622776601683794}
12 0.784165 ... {'lr__C': 0.01}
13 0.775887 ... {'lr__C': 0.03162277660168379}
14 0.771196 ... {'lr__C': 0.1}
15 0.768408 ... {'lr__C': 0.31622776601683794}
16 0.766545 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.045318
Min_out+ 0.011037
NegLpNorm_relu_0+ 0.010584
PosLpNorm_relu_0+ 0.012787
NegLpNorm_relu_1+ 0.013094
...
PosLpNorm_relu_48- 0.016872
NegLpNorm_relu_49- 0.014870
PosLpNorm_relu_49- 0.021146
NegLpNorm_relu_50- 0.044202
PosLpNorm_relu_50- 0.036723
Length: 208, dtype: float64
Split L3
Fitting Logistic Regression
mean_test_score ... params
0 0.789483 ... {'lr__C': 1e-08}
1 0.790616 ... {'lr__C': 3.162277660168379e-08}
2 0.794071 ... {'lr__C': 1e-07}
3 0.803851 ... {'lr__C': 3.162277660168379e-07}
4 0.823606 ... {'lr__C': 1e-06}
5 0.844192 ... {'lr__C': 3.162277660168379e-06}
6 0.853836 ... {'lr__C': 1e-05}
7 0.856556 ... {'lr__C': 3.1622776601683795e-05}
8 0.847674 ... {'lr__C': 0.0001}
9 0.829883 ... {'lr__C': 0.00031622776601683794}
10 0.814283 ... {'lr__C': 0.001}
11 0.800605 ... {'lr__C': 0.0031622776601683794}
12 0.789057 ... {'lr__C': 0.01}
13 0.781077 ... {'lr__C': 0.03162277660168379}
14 0.776054 ... {'lr__C': 0.1}
15 0.772773 ... {'lr__C': 0.31622776601683794}
16 0.770758 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.044040
Min_out+ 0.009710
NegLpNorm_relu_0+ 0.011054
PosLpNorm_relu_0+ 0.013779
NegLpNorm_relu_1+ 0.013514
...
PosLpNorm_relu_48- 0.017497
NegLpNorm_relu_49- 0.013840
PosLpNorm_relu_49- 0.029724
NegLpNorm_relu_50- 0.040832
PosLpNorm_relu_50- 0.038516
Length: 208, dtype: float64
======== svhn =========
======== resnet =========
Min & Max
Creating Calibration Set
Creating Augmented Set
Creating Mixed Up Set
Creating Noisy Set
Creating Shifted Set
Creating Blurry Set
Creating Shifted Set
Fitting Logistic Regression
mean_test_score ... params
0 0.863300 ... {'lr__C': 1e-08}
1 0.863370 ... {'lr__C': 3.162277660168379e-08}
2 0.863573 ... {'lr__C': 1e-07}
3 0.864226 ... {'lr__C': 3.162277660168379e-07}
4 0.865542 ... {'lr__C': 1e-06}
5 0.867553 ... {'lr__C': 3.162277660168379e-06}
6 0.868669 ... {'lr__C': 1e-05}
7 0.865718 ... {'lr__C': 3.1622776601683795e-05}
8 0.860397 ... {'lr__C': 0.0001}
9 0.854330 ... {'lr__C': 0.00031622776601683794}
10 0.847478 ... {'lr__C': 0.001}
11 0.840760 ... {'lr__C': 0.0031622776601683794}
12 0.835842 ... {'lr__C': 0.01}
13 0.833137 ... {'lr__C': 0.03162277660168379}
14 0.831991 ... {'lr__C': 0.1}
15 0.831568 ... {'lr__C': 0.31622776601683794}
16 0.831426 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.029477
Min_out+ 0.064169
Min_relu_32+ 0.011698
Max_relu_32+ 0.013338
Min_relu_0+ 0.002985
...
Max_relu_29- 0.051507
Min_relu_30- 0.040144
Max_relu_30- 0.005603
Min_relu_31- -0.029976
Max_relu_31- 0.016357
Length: 136, dtype: float64
Min
Fitting Logistic Regression
mean_test_score ... params
0 0.867574 ... {'lr__C': 1e-08}
1 0.867611 ... {'lr__C': 3.162277660168379e-08}
2 0.867732 ... {'lr__C': 1e-07}
3 0.868071 ... {'lr__C': 3.162277660168379e-07}
4 0.868887 ... {'lr__C': 1e-06}
5 0.870327 ... {'lr__C': 3.162277660168379e-06}
6 0.871321 ... {'lr__C': 1e-05}
7 0.869599 ... {'lr__C': 3.1622776601683795e-05}
8 0.864730 ... {'lr__C': 0.0001}
9 0.858909 ... {'lr__C': 0.00031622776601683794}
10 0.852747 ... {'lr__C': 0.001}
11 0.847164 ... {'lr__C': 0.0031622776601683794}
12 0.843504 ... {'lr__C': 0.01}
13 0.841744 ... {'lr__C': 0.03162277660168379}
14 0.841080 ... {'lr__C': 0.1}
15 0.840850 ... {'lr__C': 0.31622776601683794}
16 0.840776 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.036641
Min_out+ 0.079500
Min_relu_32+ 0.024425
Min_relu_0+ 0.011103
Min_relu_1+ 0.018350
...
Min_relu_27- 0.041145
Min_relu_28- 0.044972
Min_relu_29- 0.039598
Min_relu_30- 0.060245
Min_relu_31- -0.037058
Length: 70, dtype: float64
Max
Fitting Logistic Regression
mean_test_score ... params
0 0.865689 ... {'lr__C': 1e-08}
1 0.865724 ... {'lr__C': 3.162277660168379e-08}
2 0.865867 ... {'lr__C': 1e-07}
3 0.866254 ... {'lr__C': 3.162277660168379e-07}
4 0.867280 ... {'lr__C': 1e-06}
5 0.869368 ... {'lr__C': 3.162277660168379e-06}
6 0.872046 ... {'lr__C': 1e-05}
7 0.872848 ... {'lr__C': 3.1622776601683795e-05}
8 0.869855 ... {'lr__C': 0.0001}
9 0.864720 ... {'lr__C': 0.00031622776601683794}
10 0.859408 ... {'lr__C': 0.001}
11 0.855069 ... {'lr__C': 0.0031622776601683794}
12 0.852083 ... {'lr__C': 0.01}
13 0.850309 ... {'lr__C': 0.03162277660168379}
14 0.849462 ... {'lr__C': 0.1}
15 0.849130 ... {'lr__C': 0.31622776601683794}
16 0.849016 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.058948
Min_out+ 0.142381
Max_relu_32+ 0.020306
Max_relu_0+ 0.007087
Max_relu_1+ 0.024852
...
Max_relu_27- 0.106988
Max_relu_28- 0.111906
Max_relu_29- 0.102037
Max_relu_30- 0.001864
Max_relu_31- 0.014453
Length: 70, dtype: float64
Positivity
Fitting Logistic Regression
mean_test_score ... params
0 0.864519 ... {'lr__C': 1e-08}
1 0.864539 ... {'lr__C': 3.162277660168379e-08}
2 0.864575 ... {'lr__C': 1e-07}
3 0.864677 ... {'lr__C': 3.162277660168379e-07}
4 0.864990 ... {'lr__C': 1e-06}
5 0.865583 ... {'lr__C': 3.162277660168379e-06}
6 0.865516 ... {'lr__C': 1e-05}
7 0.862923 ... {'lr__C': 3.1622776601683795e-05}
8 0.855975 ... {'lr__C': 0.0001}
9 0.844603 ... {'lr__C': 0.00031622776601683794}
10 0.830920 ... {'lr__C': 0.001}
11 0.818588 ... {'lr__C': 0.0031622776601683794}
12 0.810302 ... {'lr__C': 0.01}
13 0.806010 ... {'lr__C': 0.03162277660168379}
14 0.804228 ... {'lr__C': 0.1}
15 0.803587 ... {'lr__C': 0.31622776601683794}
16 0.803366 ... {'lr__C': 1.0}
[17 rows x 4 columns]
Max_out+ -0.017773
Min_out+ 0.037217
Positivity_relu_32+ -0.005183
Positivity_relu_0+ -0.005643
Positivity_relu_1+ 0.006537
...
Positivity_relu_27- -0.016606
Positivity_relu_28- -0.011566
Positivity_relu_29- -0.018837
Positivity_relu_30- -0.017231
Positivity_relu_31- -0.018990
Length: 70, dtype: float64