ConvGeNBenchmarkResults/data_result/SimpleGAN/imblearn_protein_homo.log

///////////////////////////////////////////
// Running SimpleGAN on imblearn_protein_homo
///////////////////////////////////////////

Load 'data_input/imblearn_protein_homo'
from imblearn
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 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28867, 24
LR fn, tp: 64, 196
LR f1 score: 0.817
LR cohens kappa score: 0.815
LR average precision score: 0.868

-> test with 'GB'
GB tn, fp: 28874, 17
GB fn, tp: 59, 201
GB f1 score: 0.841
GB cohens kappa score: 0.840

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 165, 95
KNN f1 score: 0.535
KNN cohens kappa score: 0.533


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28883, 8
LR fn, tp: 59, 201
LR f1 score: 0.857
LR cohens kappa score: 0.856
LR average precision score: 0.889

-> test with 'GB'
GB tn, fp: 28886, 5
GB fn, tp: 56, 204
GB f1 score: 0.870
GB cohens kappa score: 0.869

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 153, 107
KNN f1 score: 0.583
KNN cohens kappa score: 0.581


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28867, 24
LR fn, tp: 58, 202
LR f1 score: 0.831
LR cohens kappa score: 0.830
LR average precision score: 0.890

-> test with 'GB'
GB tn, fp: 28885, 6
GB fn, tp: 71, 189
GB f1 score: 0.831
GB cohens kappa score: 0.829

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 178, 82
KNN f1 score: 0.478
KNN cohens kappa score: 0.476


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28877, 14
LR fn, tp: 69, 191
LR f1 score: 0.822
LR cohens kappa score: 0.820
LR average precision score: 0.857

-> test with 'GB'
GB tn, fp: 28883, 8
GB fn, tp: 72, 188
GB f1 score: 0.825
GB cohens kappa score: 0.823

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 166, 94
KNN f1 score: 0.530
KNN cohens kappa score: 0.527


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114524 synthetic samples
-> test with 'LR'
LR tn, fp: 28879, 12
LR fn, tp: 82, 174
LR f1 score: 0.787
LR cohens kappa score: 0.786
LR average precision score: 0.831

-> test with 'GB'
GB tn, fp: 28880, 11
GB fn, tp: 85, 171
GB f1 score: 0.781
GB cohens kappa score: 0.779

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 177, 79
KNN f1 score: 0.472
KNN cohens kappa score: 0.469


====== 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 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28880, 11
LR fn, tp: 74, 186
LR f1 score: 0.814
LR cohens kappa score: 0.813
LR average precision score: 0.871

-> test with 'GB'
GB tn, fp: 28886, 5
GB fn, tp: 79, 181
GB f1 score: 0.812
GB cohens kappa score: 0.810

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 167, 93
KNN f1 score: 0.527
KNN cohens kappa score: 0.525


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28869, 22
LR fn, tp: 60, 200
LR f1 score: 0.830
LR cohens kappa score: 0.828
LR average precision score: 0.894

-> test with 'GB'
GB tn, fp: 28880, 11
GB fn, tp: 58, 202
GB f1 score: 0.854
GB cohens kappa score: 0.853

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 164, 96
KNN f1 score: 0.539
KNN cohens kappa score: 0.537


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28871, 20
LR fn, tp: 63, 197
LR f1 score: 0.826
LR cohens kappa score: 0.825
LR average precision score: 0.835

-> test with 'GB'
GB tn, fp: 28880, 11
GB fn, tp: 71, 189
GB f1 score: 0.822
GB cohens kappa score: 0.820

-> test with 'KNN'
KNN tn, fp: 28889, 2
KNN fn, tp: 162, 98
KNN f1 score: 0.544
KNN cohens kappa score: 0.542


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28868, 23
LR fn, tp: 68, 192
LR f1 score: 0.808
LR cohens kappa score: 0.807
LR average precision score: 0.856

-> test with 'GB'
GB tn, fp: 28877, 14
GB fn, tp: 67, 193
GB f1 score: 0.827
GB cohens kappa score: 0.825

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 163, 97
KNN f1 score: 0.543
KNN cohens kappa score: 0.541


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114524 synthetic samples
-> test with 'LR'
LR tn, fp: 28875, 16
LR fn, tp: 66, 190
LR f1 score: 0.823
LR cohens kappa score: 0.821
LR average precision score: 0.868

-> test with 'GB'
GB tn, fp: 28876, 15
GB fn, tp: 69, 187
GB f1 score: 0.817
GB cohens kappa score: 0.815

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 169, 87
KNN f1 score: 0.506
KNN cohens kappa score: 0.504


====== 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 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28874, 17
LR fn, tp: 68, 192
LR f1 score: 0.819
LR cohens kappa score: 0.817
LR average precision score: 0.869

-> test with 'GB'
GB tn, fp: 28876, 15
GB fn, tp: 71, 189
GB f1 score: 0.815
GB cohens kappa score: 0.813

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 175, 85
KNN f1 score: 0.493
KNN cohens kappa score: 0.491


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28877, 14
LR fn, tp: 66, 194
LR f1 score: 0.829
LR cohens kappa score: 0.828
LR average precision score: 0.861

-> test with 'GB'
GB tn, fp: 28879, 12
GB fn, tp: 68, 192
GB f1 score: 0.828
GB cohens kappa score: 0.826

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 174, 86
KNN f1 score: 0.496
KNN cohens kappa score: 0.493


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28866, 25
LR fn, tp: 71, 189
LR f1 score: 0.797
LR cohens kappa score: 0.796
LR average precision score: 0.834

-> test with 'GB'
GB tn, fp: 28880, 11
GB fn, tp: 74, 186
GB f1 score: 0.814
GB cohens kappa score: 0.813

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 167, 93
KNN f1 score: 0.525
KNN cohens kappa score: 0.523


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28880, 11
LR fn, tp: 70, 190
LR f1 score: 0.824
LR cohens kappa score: 0.823
LR average precision score: 0.873

-> test with 'GB'
GB tn, fp: 28880, 11
GB fn, tp: 72, 188
GB f1 score: 0.819
GB cohens kappa score: 0.818

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 171, 89
KNN f1 score: 0.509
KNN cohens kappa score: 0.506


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114524 synthetic samples
-> test with 'LR'
LR tn, fp: 28873, 18
LR fn, tp: 65, 191
LR f1 score: 0.822
LR cohens kappa score: 0.820
LR average precision score: 0.874

-> test with 'GB'
GB tn, fp: 28879, 12
GB fn, tp: 64, 192
GB f1 score: 0.835
GB cohens kappa score: 0.833

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 152, 104
KNN f1 score: 0.578
KNN cohens kappa score: 0.576


====== 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 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28872, 19
LR fn, tp: 68, 192
LR f1 score: 0.815
LR cohens kappa score: 0.814
LR average precision score: 0.871

-> test with 'GB'
GB tn, fp: 28882, 9
GB fn, tp: 64, 196
GB f1 score: 0.843
GB cohens kappa score: 0.842

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 167, 93
KNN f1 score: 0.527
KNN cohens kappa score: 0.525


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28871, 20
LR fn, tp: 74, 186
LR f1 score: 0.798
LR cohens kappa score: 0.797
LR average precision score: 0.841

-> test with 'GB'
GB tn, fp: 28868, 23
GB fn, tp: 75, 185
GB f1 score: 0.791
GB cohens kappa score: 0.789

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 166, 94
KNN f1 score: 0.531
KNN cohens kappa score: 0.529


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28882, 9
LR fn, tp: 60, 200
LR f1 score: 0.853
LR cohens kappa score: 0.852
LR average precision score: 0.854

-> test with 'GB'
GB tn, fp: 28875, 16
GB fn, tp: 61, 199
GB f1 score: 0.838
GB cohens kappa score: 0.837

-> test with 'KNN'
KNN tn, fp: 28889, 2
KNN fn, tp: 175, 85
KNN f1 score: 0.490
KNN cohens kappa score: 0.488


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28875, 16
LR fn, tp: 68, 192
LR f1 score: 0.821
LR cohens kappa score: 0.819
LR average precision score: 0.871

-> test with 'GB'
GB tn, fp: 28877, 14
GB fn, tp: 68, 192
GB f1 score: 0.824
GB cohens kappa score: 0.823

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 162, 98
KNN f1 score: 0.547
KNN cohens kappa score: 0.545


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114524 synthetic samples
-> test with 'LR'
LR tn, fp: 28875, 16
LR fn, tp: 64, 192
LR f1 score: 0.828
LR cohens kappa score: 0.826
LR average precision score: 0.861

-> test with 'GB'
GB tn, fp: 28879, 12
GB fn, tp: 67, 189
GB f1 score: 0.827
GB cohens kappa score: 0.826

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 162, 94
KNN f1 score: 0.536
KNN cohens kappa score: 0.533


====== 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 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28869, 22
LR fn, tp: 65, 195
LR f1 score: 0.818
LR cohens kappa score: 0.816
LR average precision score: 0.865

-> test with 'GB'
GB tn, fp: 28878, 13
GB fn, tp: 65, 195
GB f1 score: 0.833
GB cohens kappa score: 0.832

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 172, 88
KNN f1 score: 0.504
KNN cohens kappa score: 0.502


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28880, 11
LR fn, tp: 70, 190
LR f1 score: 0.824
LR cohens kappa score: 0.823
LR average precision score: 0.862

-> test with 'GB'
GB tn, fp: 28879, 12
GB fn, tp: 73, 187
GB f1 score: 0.815
GB cohens kappa score: 0.813

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 166, 94
KNN f1 score: 0.531
KNN cohens kappa score: 0.529


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28874, 17
LR fn, tp: 72, 188
LR f1 score: 0.809
LR cohens kappa score: 0.807
LR average precision score: 0.867

-> test with 'GB'
GB tn, fp: 28882, 9
GB fn, tp: 74, 186
GB f1 score: 0.818
GB cohens kappa score: 0.816

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 168, 92
KNN f1 score: 0.523
KNN cohens kappa score: 0.520


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114528 synthetic samples
-> test with 'LR'
LR tn, fp: 28874, 17
LR fn, tp: 65, 195
LR f1 score: 0.826
LR cohens kappa score: 0.825
LR average precision score: 0.876

-> test with 'GB'
GB tn, fp: 28878, 13
GB fn, tp: 71, 189
GB f1 score: 0.818
GB cohens kappa score: 0.817

-> test with 'KNN'
KNN tn, fp: 28891, 0
KNN fn, tp: 173, 87
KNN f1 score: 0.501
KNN cohens kappa score: 0.499


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 114524 synthetic samples
-> test with 'LR'
LR tn, fp: 28871, 20
LR fn, tp: 64, 192
LR f1 score: 0.821
LR cohens kappa score: 0.819
LR average precision score: 0.850

-> test with 'GB'
GB tn, fp: 28884, 7
GB fn, tp: 63, 193
GB f1 score: 0.846
GB cohens kappa score: 0.845

-> test with 'KNN'
KNN tn, fp: 28890, 1
KNN fn, tp: 156, 100
KNN f1 score: 0.560
KNN cohens kappa score: 0.558

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 28883, 25
LR fn, tp: 82, 202
LR f1 score: 0.857
LR cohens kappa score: 0.856
LR average precision score: 0.894


average:
LR tn, fp: 28873.96, 17.04
LR fn, tp: 66.92, 192.28
LR f1 score: 0.821
LR cohens kappa score: 0.819
LR average precision score: 0.863


minimum:
LR tn, fp: 28866, 8
LR fn, tp: 58, 174
LR f1 score: 0.787
LR cohens kappa score: 0.786
LR average precision score: 0.831


-----[ GB ]-----
maximum:
GB tn, fp: 28886, 23
GB fn, tp: 85, 204
GB f1 score: 0.870
GB cohens kappa score: 0.869


average:
GB tn, fp: 28879.32, 11.68
GB fn, tp: 68.68, 190.52
GB f1 score: 0.826
GB cohens kappa score: 0.824


minimum:
GB tn, fp: 28868, 5
GB fn, tp: 56, 171
GB f1 score: 0.781
GB cohens kappa score: 0.779


-----[ KNN ]-----
maximum:
KNN tn, fp: 28891, 2
KNN fn, tp: 178, 107
KNN f1 score: 0.583
KNN cohens kappa score: 0.581


average:
KNN tn, fp: 28890.48, 0.52
KNN fn, tp: 166.8, 92.4
KNN f1 score: 0.524
KNN cohens kappa score: 0.522


minimum:
KNN tn, fp: 28889, 0
KNN fn, tp: 152, 79
KNN f1 score: 0.472
KNN cohens kappa score: 0.469