ConvGeNBenchmarkResults/data_result/SimpleGAN/imblearn_mammography.log

///////////////////////////////////////////
// Running SimpleGAN on imblearn_mammography
///////////////////////////////////////////

Load 'data_input/imblearn_mammography'
from imblearn
non empty cut in data_input/imblearn_mammography! (7 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 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2095, 90
LR fn, tp: 13, 39
LR f1 score: 0.431
LR cohens kappa score: 0.411
LR average precision score: 0.608

-> test with 'GB'
GB tn, fp: 2154, 31
GB fn, tp: 22, 30
GB f1 score: 0.531
GB cohens kappa score: 0.519

-> test with 'KNN'
KNN tn, fp: 1483, 702
KNN fn, tp: 21, 31
KNN f1 score: 0.079
KNN cohens kappa score: 0.037


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2143, 42
LR fn, tp: 22, 30
LR f1 score: 0.484
LR cohens kappa score: 0.470
LR average precision score: 0.508

-> test with 'GB'
GB tn, fp: 2184, 1
GB fn, tp: 24, 28
GB f1 score: 0.691
GB cohens kappa score: 0.686

-> test with 'KNN'
KNN tn, fp: 2183, 2
KNN fn, tp: 30, 22
KNN f1 score: 0.579
KNN cohens kappa score: 0.573


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2068, 117
LR fn, tp: 11, 41
LR f1 score: 0.390
LR cohens kappa score: 0.368
LR average precision score: 0.536

-> test with 'GB'
GB tn, fp: 2174, 11
GB fn, tp: 14, 38
GB f1 score: 0.752
GB cohens kappa score: 0.747

-> test with 'KNN'
KNN tn, fp: 2175, 10
KNN fn, tp: 20, 32
KNN f1 score: 0.681
KNN cohens kappa score: 0.674


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2128, 57
LR fn, tp: 25, 27
LR f1 score: 0.397
LR cohens kappa score: 0.379
LR average precision score: 0.343

-> test with 'GB'
GB tn, fp: 2176, 9
GB fn, tp: 26, 26
GB f1 score: 0.598
GB cohens kappa score: 0.590

-> test with 'KNN'
KNN tn, fp: 2176, 9
KNN fn, tp: 31, 21
KNN f1 score: 0.512
KNN cohens kappa score: 0.504


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8532 synthetic samples
-> test with 'LR'
LR tn, fp: 2152, 31
LR fn, tp: 26, 26
LR f1 score: 0.477
LR cohens kappa score: 0.464
LR average precision score: 0.498

-> test with 'GB'
GB tn, fp: 2174, 9
GB fn, tp: 23, 29
GB f1 score: 0.644
GB cohens kappa score: 0.637

-> test with 'KNN'
KNN tn, fp: 1568, 615
KNN fn, tp: 27, 25
KNN f1 score: 0.072
KNN cohens kappa score: 0.031


====== 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 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2152, 33
LR fn, tp: 27, 25
LR f1 score: 0.455
LR cohens kappa score: 0.441
LR average precision score: 0.462

-> test with 'GB'
GB tn, fp: 2178, 7
GB fn, tp: 25, 27
GB f1 score: 0.628
GB cohens kappa score: 0.621

-> test with 'KNN'
KNN tn, fp: 2179, 6
KNN fn, tp: 22, 30
KNN f1 score: 0.682
KNN cohens kappa score: 0.676


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2071, 114
LR fn, tp: 17, 35
LR f1 score: 0.348
LR cohens kappa score: 0.325
LR average precision score: 0.453

-> test with 'GB'
GB tn, fp: 2170, 15
GB fn, tp: 23, 29
GB f1 score: 0.604
GB cohens kappa score: 0.596

-> test with 'KNN'
KNN tn, fp: 2180, 5
KNN fn, tp: 26, 26
KNN f1 score: 0.627
KNN cohens kappa score: 0.620


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2164, 21
LR fn, tp: 24, 28
LR f1 score: 0.554
LR cohens kappa score: 0.544
LR average precision score: 0.571

-> test with 'GB'
GB tn, fp: 2179, 6
GB fn, tp: 26, 26
GB f1 score: 0.619
GB cohens kappa score: 0.612

-> test with 'KNN'
KNN tn, fp: 1522, 663
KNN fn, tp: 28, 24
KNN f1 score: 0.065
KNN cohens kappa score: 0.023


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2163, 22
LR fn, tp: 22, 30
LR f1 score: 0.577
LR cohens kappa score: 0.567
LR average precision score: 0.606

-> test with 'GB'
GB tn, fp: 2176, 9
GB fn, tp: 25, 27
GB f1 score: 0.614
GB cohens kappa score: 0.606

-> test with 'KNN'
KNN tn, fp: 2180, 5
KNN fn, tp: 30, 22
KNN f1 score: 0.557
KNN cohens kappa score: 0.550


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8532 synthetic samples
-> test with 'LR'
LR tn, fp: 2132, 51
LR fn, tp: 20, 32
LR f1 score: 0.474
LR cohens kappa score: 0.459
LR average precision score: 0.478

-> test with 'GB'
GB tn, fp: 2175, 8
GB fn, tp: 29, 23
GB f1 score: 0.554
GB cohens kappa score: 0.546

-> test with 'KNN'
KNN tn, fp: 2177, 6
KNN fn, tp: 32, 20
KNN f1 score: 0.513
KNN cohens kappa score: 0.505


====== 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 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2119, 66
LR fn, tp: 13, 39
LR f1 score: 0.497
LR cohens kappa score: 0.481
LR average precision score: 0.657

-> test with 'GB'
GB tn, fp: 2184, 1
GB fn, tp: 17, 35
GB f1 score: 0.795
GB cohens kappa score: 0.791

-> test with 'KNN'
KNN tn, fp: 2182, 3
KNN fn, tp: 20, 32
KNN f1 score: 0.736
KNN cohens kappa score: 0.731


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2154, 31
LR fn, tp: 20, 32
LR f1 score: 0.557
LR cohens kappa score: 0.545
LR average precision score: 0.548

-> test with 'GB'
GB tn, fp: 2173, 12
GB fn, tp: 27, 25
GB f1 score: 0.562
GB cohens kappa score: 0.553

-> test with 'KNN'
KNN tn, fp: 2177, 8
KNN fn, tp: 30, 22
KNN f1 score: 0.537
KNN cohens kappa score: 0.529


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2162, 23
LR fn, tp: 24, 28
LR f1 score: 0.544
LR cohens kappa score: 0.533
LR average precision score: 0.603

-> test with 'GB'
GB tn, fp: 2180, 5
GB fn, tp: 23, 29
GB f1 score: 0.674
GB cohens kappa score: 0.668

-> test with 'KNN'
KNN tn, fp: 2181, 4
KNN fn, tp: 28, 24
KNN f1 score: 0.600
KNN cohens kappa score: 0.593


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2143, 42
LR fn, tp: 17, 35
LR f1 score: 0.543
LR cohens kappa score: 0.530
LR average precision score: 0.506

-> test with 'GB'
GB tn, fp: 2177, 8
GB fn, tp: 25, 27
GB f1 score: 0.621
GB cohens kappa score: 0.613

-> test with 'KNN'
KNN tn, fp: 2176, 9
KNN fn, tp: 26, 26
KNN f1 score: 0.598
KNN cohens kappa score: 0.590


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8532 synthetic samples
-> test with 'LR'
LR tn, fp: 2000, 183
LR fn, tp: 23, 29
LR f1 score: 0.220
LR cohens kappa score: 0.189
LR average precision score: 0.145

-> test with 'GB'
GB tn, fp: 2174, 9
GB fn, tp: 28, 24
GB f1 score: 0.565
GB cohens kappa score: 0.557

-> test with 'KNN'
KNN tn, fp: 2173, 10
KNN fn, tp: 30, 22
KNN f1 score: 0.524
KNN cohens kappa score: 0.515


====== 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 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2173, 12
LR fn, tp: 28, 24
LR f1 score: 0.545
LR cohens kappa score: 0.537
LR average precision score: 0.580

-> test with 'GB'
GB tn, fp: 2179, 6
GB fn, tp: 25, 27
GB f1 score: 0.635
GB cohens kappa score: 0.629

-> test with 'KNN'
KNN tn, fp: 2181, 4
KNN fn, tp: 27, 25
KNN f1 score: 0.617
KNN cohens kappa score: 0.611


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2174, 11
LR fn, tp: 23, 29
LR f1 score: 0.630
LR cohens kappa score: 0.623
LR average precision score: 0.622

-> test with 'GB'
GB tn, fp: 2179, 6
GB fn, tp: 20, 32
GB f1 score: 0.711
GB cohens kappa score: 0.705

-> test with 'KNN'
KNN tn, fp: 2181, 4
KNN fn, tp: 26, 26
KNN f1 score: 0.634
KNN cohens kappa score: 0.628


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2047, 138
LR fn, tp: 10, 42
LR f1 score: 0.362
LR cohens kappa score: 0.338
LR average precision score: 0.621

-> test with 'GB'
GB tn, fp: 2168, 17
GB fn, tp: 16, 36
GB f1 score: 0.686
GB cohens kappa score: 0.678

-> test with 'KNN'
KNN tn, fp: 2162, 23
KNN fn, tp: 22, 30
KNN f1 score: 0.571
KNN cohens kappa score: 0.561


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2154, 31
LR fn, tp: 25, 27
LR f1 score: 0.491
LR cohens kappa score: 0.478
LR average precision score: 0.496

-> test with 'GB'
GB tn, fp: 2179, 6
GB fn, tp: 23, 29
GB f1 score: 0.667
GB cohens kappa score: 0.660

-> test with 'KNN'
KNN tn, fp: 2180, 5
KNN fn, tp: 29, 23
KNN f1 score: 0.575
KNN cohens kappa score: 0.568


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8532 synthetic samples
-> test with 'LR'
LR tn, fp: 2160, 23
LR fn, tp: 26, 26
LR f1 score: 0.515
LR cohens kappa score: 0.504
LR average precision score: 0.490

-> test with 'GB'
GB tn, fp: 2175, 8
GB fn, tp: 21, 31
GB f1 score: 0.681
GB cohens kappa score: 0.675

-> test with 'KNN'
KNN tn, fp: 2177, 6
KNN fn, tp: 25, 27
KNN f1 score: 0.635
KNN cohens kappa score: 0.629


====== 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 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2158, 27
LR fn, tp: 17, 35
LR f1 score: 0.614
LR cohens kappa score: 0.604
LR average precision score: 0.629

-> test with 'GB'
GB tn, fp: 2180, 5
GB fn, tp: 22, 30
GB f1 score: 0.690
GB cohens kappa score: 0.684

-> test with 'KNN'
KNN tn, fp: 2180, 5
KNN fn, tp: 25, 27
KNN f1 score: 0.643
KNN cohens kappa score: 0.636


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2166, 19
LR fn, tp: 23, 29
LR f1 score: 0.580
LR cohens kappa score: 0.570
LR average precision score: 0.557

-> test with 'GB'
GB tn, fp: 2176, 9
GB fn, tp: 25, 27
GB f1 score: 0.614
GB cohens kappa score: 0.606

-> test with 'KNN'
KNN tn, fp: 1509, 676
KNN fn, tp: 27, 25
KNN f1 score: 0.066
KNN cohens kappa score: 0.024


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2112, 73
LR fn, tp: 15, 37
LR f1 score: 0.457
LR cohens kappa score: 0.439
LR average precision score: 0.549

-> test with 'GB'
GB tn, fp: 2169, 16
GB fn, tp: 25, 27
GB f1 score: 0.568
GB cohens kappa score: 0.559

-> test with 'KNN'
KNN tn, fp: 2169, 16
KNN fn, tp: 26, 26
KNN f1 score: 0.553
KNN cohens kappa score: 0.544


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8530 synthetic samples
-> test with 'LR'
LR tn, fp: 2114, 71
LR fn, tp: 12, 40
LR f1 score: 0.491
LR cohens kappa score: 0.474
LR average precision score: 0.592

-> test with 'GB'
GB tn, fp: 2164, 21
GB fn, tp: 15, 37
GB f1 score: 0.673
GB cohens kappa score: 0.665

-> test with 'KNN'
KNN tn, fp: 2173, 12
KNN fn, tp: 18, 34
KNN f1 score: 0.694
KNN cohens kappa score: 0.687


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 8532 synthetic samples
-> test with 'LR'
LR tn, fp: 2169, 14
LR fn, tp: 24, 28
LR f1 score: 0.596
LR cohens kappa score: 0.587
LR average precision score: 0.614

-> test with 'GB'
GB tn, fp: 2175, 8
GB fn, tp: 22, 30
GB f1 score: 0.667
GB cohens kappa score: 0.660

-> test with 'KNN'
KNN tn, fp: 2180, 3
KNN fn, tp: 28, 24
KNN f1 score: 0.608
KNN cohens kappa score: 0.601

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 2174, 183
LR fn, tp: 28, 42
LR f1 score: 0.630
LR cohens kappa score: 0.623
LR average precision score: 0.657


average:
LR tn, fp: 2130.92, 53.68
LR fn, tp: 20.28, 31.72
LR f1 score: 0.489
LR cohens kappa score: 0.474
LR average precision score: 0.531


minimum:
LR tn, fp: 2000, 11
LR fn, tp: 10, 24
LR f1 score: 0.220
LR cohens kappa score: 0.189
LR average precision score: 0.145


-----[ GB ]-----
maximum:
GB tn, fp: 2184, 31
GB fn, tp: 29, 38
GB f1 score: 0.795
GB cohens kappa score: 0.791


average:
GB tn, fp: 2174.88, 9.72
GB fn, tp: 22.84, 29.16
GB f1 score: 0.642
GB cohens kappa score: 0.635


minimum:
GB tn, fp: 2154, 1
GB fn, tp: 14, 23
GB f1 score: 0.531
GB cohens kappa score: 0.519


-----[ KNN ]-----
maximum:
KNN tn, fp: 2183, 702
KNN fn, tp: 32, 34
KNN f1 score: 0.736
KNN cohens kappa score: 0.731


average:
KNN tn, fp: 2072.16, 112.44
KNN fn, tp: 26.16, 25.84
KNN f1 score: 0.518
KNN cohens kappa score: 0.506


minimum:
KNN tn, fp: 1483, 2
KNN fn, tp: 18, 20
KNN f1 score: 0.065
KNN cohens kappa score: 0.023