ConvGeNBenchmarkResults/data_result/SimpleGAN/imblearn_webpage.log

///////////////////////////////////////////
// Running SimpleGAN on imblearn_webpage
///////////////////////////////////////////

Load 'data_input/imblearn_webpage'
from imblearn
non empty cut in data_input/imblearn_webpage! (76 points)
Data loaded.
-> Shuffling data
### Start exercise for synthetic point generator

====== Step 1/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 1/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6726, 34
LR fn, tp: 60, 137
LR f1 score: 0.745
LR cohens kappa score: 0.738
LR average precision score: 0.797

-> test with 'GB'
GB tn, fp: 6755, 5
GB fn, tp: 88, 109
GB f1 score: 0.701
GB cohens kappa score: 0.695

-> test with 'KNN'
KNN tn, fp: 6753, 7
KNN fn, tp: 114, 83
KNN f1 score: 0.578
KNN cohens kappa score: 0.571


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6729, 31
LR fn, tp: 55, 142
LR f1 score: 0.768
LR cohens kappa score: 0.761
LR average precision score: 0.815

-> test with 'GB'
GB tn, fp: 6754, 6
GB fn, tp: 86, 111
GB f1 score: 0.707
GB cohens kappa score: 0.701

-> test with 'KNN'
KNN tn, fp: 6757, 3
KNN fn, tp: 117, 80
KNN f1 score: 0.571
KNN cohens kappa score: 0.564


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6740, 20
LR fn, tp: 52, 145
LR f1 score: 0.801
LR cohens kappa score: 0.796
LR average precision score: 0.848

-> test with 'GB'
GB tn, fp: 6755, 5
GB fn, tp: 82, 115
GB f1 score: 0.726
GB cohens kappa score: 0.720

-> test with 'KNN'
KNN tn, fp: 6760, 0
KNN fn, tp: 112, 85
KNN f1 score: 0.603
KNN cohens kappa score: 0.596


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6733, 27
LR fn, tp: 60, 137
LR f1 score: 0.759
LR cohens kappa score: 0.753
LR average precision score: 0.793

-> test with 'GB'
GB tn, fp: 6752, 8
GB fn, tp: 93, 104
GB f1 score: 0.673
GB cohens kappa score: 0.666

-> test with 'KNN'
KNN tn, fp: 6752, 8
KNN fn, tp: 123, 74
KNN f1 score: 0.530
KNN cohens kappa score: 0.523


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26252 synthetic samples
-> test with 'LR'
LR tn, fp: 6724, 35
LR fn, tp: 58, 135
LR f1 score: 0.744
LR cohens kappa score: 0.737
LR average precision score: 0.780

-> test with 'GB'
GB tn, fp: 6749, 10
GB fn, tp: 89, 104
GB f1 score: 0.678
GB cohens kappa score: 0.671

-> test with 'KNN'
KNN tn, fp: 6756, 3
KNN fn, tp: 122, 71
KNN f1 score: 0.532
KNN cohens kappa score: 0.525


====== Step 2/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6736, 24
LR fn, tp: 66, 131
LR f1 score: 0.744
LR cohens kappa score: 0.738
LR average precision score: 0.820

-> test with 'GB'
GB tn, fp: 6755, 5
GB fn, tp: 83, 114
GB f1 score: 0.722
GB cohens kappa score: 0.715

-> test with 'KNN'
KNN tn, fp: 6755, 5
KNN fn, tp: 121, 76
KNN f1 score: 0.547
KNN cohens kappa score: 0.539


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6734, 26
LR fn, tp: 55, 142
LR f1 score: 0.778
LR cohens kappa score: 0.772
LR average precision score: 0.831

-> test with 'GB'
GB tn, fp: 6752, 8
GB fn, tp: 85, 112
GB f1 score: 0.707
GB cohens kappa score: 0.700

-> test with 'KNN'
KNN tn, fp: 6753, 7
KNN fn, tp: 124, 73
KNN f1 score: 0.527
KNN cohens kappa score: 0.519


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6726, 34
LR fn, tp: 56, 141
LR f1 score: 0.758
LR cohens kappa score: 0.751
LR average precision score: 0.787

-> test with 'GB'
GB tn, fp: 6754, 6
GB fn, tp: 86, 111
GB f1 score: 0.707
GB cohens kappa score: 0.701

-> test with 'KNN'
KNN tn, fp: 6756, 4
KNN fn, tp: 114, 83
KNN f1 score: 0.585
KNN cohens kappa score: 0.577


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6726, 34
LR fn, tp: 64, 133
LR f1 score: 0.731
LR cohens kappa score: 0.724
LR average precision score: 0.801

-> test with 'GB'
GB tn, fp: 6756, 4
GB fn, tp: 95, 102
GB f1 score: 0.673
GB cohens kappa score: 0.667

-> test with 'KNN'
KNN tn, fp: 6759, 1
KNN fn, tp: 113, 84
KNN f1 score: 0.596
KNN cohens kappa score: 0.589


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26252 synthetic samples
-> test with 'LR'
LR tn, fp: 6741, 18
LR fn, tp: 60, 133
LR f1 score: 0.773
LR cohens kappa score: 0.768
LR average precision score: 0.823

-> test with 'GB'
GB tn, fp: 6754, 5
GB fn, tp: 84, 109
GB f1 score: 0.710
GB cohens kappa score: 0.704

-> test with 'KNN'
KNN tn, fp: 6758, 1
KNN fn, tp: 124, 69
KNN f1 score: 0.525
KNN cohens kappa score: 0.518


====== Step 3/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6723, 37
LR fn, tp: 57, 140
LR f1 score: 0.749
LR cohens kappa score: 0.742
LR average precision score: 0.781

-> test with 'GB'
GB tn, fp: 6751, 9
GB fn, tp: 83, 114
GB f1 score: 0.712
GB cohens kappa score: 0.706

-> test with 'KNN'
KNN tn, fp: 6759, 1
KNN fn, tp: 121, 76
KNN f1 score: 0.555
KNN cohens kappa score: 0.548


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6738, 22
LR fn, tp: 56, 141
LR f1 score: 0.783
LR cohens kappa score: 0.778
LR average precision score: 0.823

-> test with 'GB'
GB tn, fp: 6755, 5
GB fn, tp: 87, 110
GB f1 score: 0.705
GB cohens kappa score: 0.699

-> test with 'KNN'
KNN tn, fp: 6757, 3
KNN fn, tp: 122, 75
KNN f1 score: 0.545
KNN cohens kappa score: 0.538


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6739, 21
LR fn, tp: 76, 121
LR f1 score: 0.714
LR cohens kappa score: 0.707
LR average precision score: 0.759

-> test with 'GB'
GB tn, fp: 6756, 4
GB fn, tp: 105, 92
GB f1 score: 0.628
GB cohens kappa score: 0.621

-> test with 'KNN'
KNN tn, fp: 6758, 2
KNN fn, tp: 132, 65
KNN f1 score: 0.492
KNN cohens kappa score: 0.485


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6724, 36
LR fn, tp: 48, 149
LR f1 score: 0.780
LR cohens kappa score: 0.774
LR average precision score: 0.857

-> test with 'GB'
GB tn, fp: 6751, 9
GB fn, tp: 84, 113
GB f1 score: 0.708
GB cohens kappa score: 0.702

-> test with 'KNN'
KNN tn, fp: 6750, 10
KNN fn, tp: 103, 94
KNN f1 score: 0.625
KNN cohens kappa score: 0.617


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26252 synthetic samples
-> test with 'LR'
LR tn, fp: 6733, 26
LR fn, tp: 59, 134
LR f1 score: 0.759
LR cohens kappa score: 0.753
LR average precision score: 0.822

-> test with 'GB'
GB tn, fp: 6759, 0
GB fn, tp: 83, 110
GB f1 score: 0.726
GB cohens kappa score: 0.720

-> test with 'KNN'
KNN tn, fp: 6757, 2
KNN fn, tp: 112, 81
KNN f1 score: 0.587
KNN cohens kappa score: 0.580


====== Step 4/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6733, 27
LR fn, tp: 56, 141
LR f1 score: 0.773
LR cohens kappa score: 0.767
LR average precision score: 0.791

-> test with 'GB'
GB tn, fp: 6753, 7
GB fn, tp: 82, 115
GB f1 score: 0.721
GB cohens kappa score: 0.715

-> test with 'KNN'
KNN tn, fp: 6759, 1
KNN fn, tp: 130, 67
KNN f1 score: 0.506
KNN cohens kappa score: 0.498


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6729, 31
LR fn, tp: 60, 137
LR f1 score: 0.751
LR cohens kappa score: 0.744
LR average precision score: 0.794

-> test with 'GB'
GB tn, fp: 6757, 3
GB fn, tp: 99, 98
GB f1 score: 0.658
GB cohens kappa score: 0.651

-> test with 'KNN'
KNN tn, fp: 6750, 10
KNN fn, tp: 117, 80
KNN f1 score: 0.557
KNN cohens kappa score: 0.549


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6733, 27
LR fn, tp: 55, 142
LR f1 score: 0.776
LR cohens kappa score: 0.770
LR average precision score: 0.828

-> test with 'GB'
GB tn, fp: 6756, 4
GB fn, tp: 95, 102
GB f1 score: 0.673
GB cohens kappa score: 0.667

-> test with 'KNN'
KNN tn, fp: 6759, 1
KNN fn, tp: 121, 76
KNN f1 score: 0.555
KNN cohens kappa score: 0.548


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6722, 38
LR fn, tp: 64, 133
LR f1 score: 0.723
LR cohens kappa score: 0.715
LR average precision score: 0.796

-> test with 'GB'
GB tn, fp: 6748, 12
GB fn, tp: 74, 123
GB f1 score: 0.741
GB cohens kappa score: 0.735

-> test with 'KNN'
KNN tn, fp: 6754, 6
KNN fn, tp: 116, 81
KNN f1 score: 0.570
KNN cohens kappa score: 0.563


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26252 synthetic samples
-> test with 'LR'
LR tn, fp: 6736, 23
LR fn, tp: 52, 141
LR f1 score: 0.790
LR cohens kappa score: 0.784
LR average precision score: 0.832

-> test with 'GB'
GB tn, fp: 6755, 4
GB fn, tp: 86, 107
GB f1 score: 0.704
GB cohens kappa score: 0.698

-> test with 'KNN'
KNN tn, fp: 6757, 2
KNN fn, tp: 113, 80
KNN f1 score: 0.582
KNN cohens kappa score: 0.575


====== Step 5/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6727, 33
LR fn, tp: 58, 139
LR f1 score: 0.753
LR cohens kappa score: 0.747
LR average precision score: 0.801

-> test with 'GB'
GB tn, fp: 6753, 7
GB fn, tp: 85, 112
GB f1 score: 0.709
GB cohens kappa score: 0.703

-> test with 'KNN'
KNN tn, fp: 6750, 10
KNN fn, tp: 112, 85
KNN f1 score: 0.582
KNN cohens kappa score: 0.574


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6734, 26
LR fn, tp: 67, 130
LR f1 score: 0.737
LR cohens kappa score: 0.730
LR average precision score: 0.768

-> test with 'GB'
GB tn, fp: 6753, 7
GB fn, tp: 93, 104
GB f1 score: 0.675
GB cohens kappa score: 0.669

-> test with 'KNN'
KNN tn, fp: 6752, 8
KNN fn, tp: 125, 72
KNN f1 score: 0.520
KNN cohens kappa score: 0.512


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6726, 34
LR fn, tp: 61, 136
LR f1 score: 0.741
LR cohens kappa score: 0.734
LR average precision score: 0.802

-> test with 'GB'
GB tn, fp: 6752, 8
GB fn, tp: 82, 115
GB f1 score: 0.719
GB cohens kappa score: 0.712

-> test with 'KNN'
KNN tn, fp: 6755, 5
KNN fn, tp: 113, 84
KNN f1 score: 0.587
KNN cohens kappa score: 0.580


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26255 synthetic samples
-> test with 'LR'
LR tn, fp: 6731, 29
LR fn, tp: 51, 146
LR f1 score: 0.785
LR cohens kappa score: 0.779
LR average precision score: 0.849

-> test with 'GB'
GB tn, fp: 6755, 5
GB fn, tp: 76, 121
GB f1 score: 0.749
GB cohens kappa score: 0.744

-> test with 'KNN'
KNN tn, fp: 6744, 16
KNN fn, tp: 119, 78
KNN f1 score: 0.536
KNN cohens kappa score: 0.527


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 26252 synthetic samples
-> test with 'LR'
LR tn, fp: 6726, 33
LR fn, tp: 69, 124
LR f1 score: 0.709
LR cohens kappa score: 0.701
LR average precision score: 0.773

-> test with 'GB'
GB tn, fp: 6754, 5
GB fn, tp: 94, 99
GB f1 score: 0.667
GB cohens kappa score: 0.660

-> test with 'KNN'
KNN tn, fp: 6757, 2
KNN fn, tp: 115, 78
KNN f1 score: 0.571
KNN cohens kappa score: 0.564

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 6741, 38
LR fn, tp: 76, 149
LR f1 score: 0.801
LR cohens kappa score: 0.796
LR average precision score: 0.857


average:
LR tn, fp: 6730.76, 29.04
LR fn, tp: 59.0, 137.2
LR f1 score: 0.757
LR cohens kappa score: 0.750
LR average precision score: 0.807


minimum:
LR tn, fp: 6722, 18
LR fn, tp: 48, 121
LR f1 score: 0.709
LR cohens kappa score: 0.701
LR average precision score: 0.759


-----[ GB ]-----
maximum:
GB tn, fp: 6759, 12
GB fn, tp: 105, 123
GB f1 score: 0.749
GB cohens kappa score: 0.744


average:
GB tn, fp: 6753.76, 6.04
GB fn, tp: 87.16, 109.04
GB f1 score: 0.700
GB cohens kappa score: 0.694


minimum:
GB tn, fp: 6748, 0
GB fn, tp: 74, 92
GB f1 score: 0.628
GB cohens kappa score: 0.621


-----[ KNN ]-----
maximum:
KNN tn, fp: 6760, 16
KNN fn, tp: 132, 94
KNN f1 score: 0.625
KNN cohens kappa score: 0.617


average:
KNN tn, fp: 6755.08, 4.72
KNN fn, tp: 118.2, 78.0
KNN f1 score: 0.559
KNN cohens kappa score: 0.551


minimum:
KNN tn, fp: 6744, 0
KNN fn, tp: 103, 65
KNN f1 score: 0.492
KNN cohens kappa score: 0.485