ConvGeNBenchmarkResults/data_result/SimpleGAN/imblearn_ozone_level.log

///////////////////////////////////////////
// Running SimpleGAN on imblearn_ozone_level
///////////////////////////////////////////

Load 'data_input/imblearn_ozone_level'
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 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 487, 6
LR fn, tp: 10, 5
LR f1 score: 0.385
LR cohens kappa score: 0.369
LR average precision score: 0.463

-> test with 'GB'
GB tn, fp: 492, 1
GB fn, tp: 11, 4
GB f1 score: 0.400
GB cohens kappa score: 0.391

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 486, 7
LR fn, tp: 11, 4
LR f1 score: 0.308
LR cohens kappa score: 0.290
LR average precision score: 0.251

-> test with 'GB'
GB tn, fp: 492, 1
GB fn, tp: 14, 1
GB f1 score: 0.118
GB cohens kappa score: 0.111

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 482, 11
LR fn, tp: 11, 4
LR f1 score: 0.267
LR cohens kappa score: 0.244
LR average precision score: 0.209

-> test with 'GB'
GB tn, fp: 490, 3
GB fn, tp: 13, 2
GB f1 score: 0.200
GB cohens kappa score: 0.188

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 486, 7
LR fn, tp: 14, 1
LR f1 score: 0.087
LR cohens kappa score: 0.068
LR average precision score: 0.212

-> test with 'GB'
GB tn, fp: 488, 5
GB fn, tp: 14, 1
GB f1 score: 0.095
GB cohens kappa score: 0.080

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 484, 7
LR fn, tp: 13, 0
LR f1 score: 0.000
LR cohens kappa score: -0.018
LR average precision score: 0.169

-> test with 'GB'
GB tn, fp: 488, 3
GB fn, tp: 13, 0
GB f1 score: 0.000
GB cohens kappa score: -0.010

-> test with 'KNN'
KNN tn, fp: 491, 0
KNN fn, tp: 13, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


====== 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 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 484, 9
LR fn, tp: 13, 2
LR f1 score: 0.154
LR cohens kappa score: 0.132
LR average precision score: 0.222

-> test with 'GB'
GB tn, fp: 489, 4
GB fn, tp: 13, 2
GB f1 score: 0.190
GB cohens kappa score: 0.177

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 488, 5
LR fn, tp: 12, 3
LR f1 score: 0.261
LR cohens kappa score: 0.245
LR average precision score: 0.205

-> test with 'GB'
GB tn, fp: 492, 1
GB fn, tp: 15, 0
GB f1 score: 0.000
GB cohens kappa score: -0.004

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 489, 4
LR fn, tp: 9, 6
LR f1 score: 0.480
LR cohens kappa score: 0.467
LR average precision score: 0.517

-> test with 'GB'
GB tn, fp: 490, 3
GB fn, tp: 14, 1
GB f1 score: 0.105
GB cohens kappa score: 0.094

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 488, 5
LR fn, tp: 14, 1
LR f1 score: 0.095
LR cohens kappa score: 0.080
LR average precision score: 0.207

-> test with 'GB'
GB tn, fp: 490, 3
GB fn, tp: 13, 2
GB f1 score: 0.200
GB cohens kappa score: 0.188

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 480, 11
LR fn, tp: 10, 3
LR f1 score: 0.222
LR cohens kappa score: 0.201
LR average precision score: 0.209

-> test with 'GB'
GB tn, fp: 489, 2
GB fn, tp: 10, 3
GB f1 score: 0.333
GB cohens kappa score: 0.324

-> test with 'KNN'
KNN tn, fp: 491, 0
KNN fn, tp: 13, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


====== 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 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 484, 9
LR fn, tp: 11, 4
LR f1 score: 0.286
LR cohens kappa score: 0.266
LR average precision score: 0.281

-> test with 'GB'
GB tn, fp: 490, 3
GB fn, tp: 14, 1
GB f1 score: 0.105
GB cohens kappa score: 0.094

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 478, 15
LR fn, tp: 14, 1
LR f1 score: 0.065
LR cohens kappa score: 0.035
LR average precision score: 0.162

-> test with 'GB'
GB tn, fp: 491, 2
GB fn, tp: 15, 0
GB f1 score: 0.000
GB cohens kappa score: -0.007

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 483, 10
LR fn, tp: 12, 3
LR f1 score: 0.214
LR cohens kappa score: 0.192
LR average precision score: 0.219

-> test with 'GB'
GB tn, fp: 490, 3
GB fn, tp: 13, 2
GB f1 score: 0.200
GB cohens kappa score: 0.188

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 489, 4
LR fn, tp: 12, 3
LR f1 score: 0.273
LR cohens kappa score: 0.259
LR average precision score: 0.271

-> test with 'GB'
GB tn, fp: 492, 1
GB fn, tp: 13, 2
GB f1 score: 0.222
GB cohens kappa score: 0.214

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 482, 9
LR fn, tp: 9, 4
LR f1 score: 0.308
LR cohens kappa score: 0.289
LR average precision score: 0.363

-> test with 'GB'
GB tn, fp: 488, 3
GB fn, tp: 12, 1
GB f1 score: 0.118
GB cohens kappa score: 0.107

-> test with 'KNN'
KNN tn, fp: 491, 0
KNN fn, tp: 13, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


====== 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 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 485, 8
LR fn, tp: 12, 3
LR f1 score: 0.231
LR cohens kappa score: 0.211
LR average precision score: 0.282

-> test with 'GB'
GB tn, fp: 490, 3
GB fn, tp: 13, 2
GB f1 score: 0.200
GB cohens kappa score: 0.188

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 484, 9
LR fn, tp: 13, 2
LR f1 score: 0.154
LR cohens kappa score: 0.132
LR average precision score: 0.209

-> test with 'GB'
GB tn, fp: 492, 1
GB fn, tp: 15, 0
GB f1 score: 0.000
GB cohens kappa score: -0.004

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 486, 7
LR fn, tp: 12, 3
LR f1 score: 0.240
LR cohens kappa score: 0.222
LR average precision score: 0.246

-> test with 'GB'
GB tn, fp: 491, 2
GB fn, tp: 12, 3
GB f1 score: 0.300
GB cohens kappa score: 0.290

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 486, 7
LR fn, tp: 8, 7
LR f1 score: 0.483
LR cohens kappa score: 0.468
LR average precision score: 0.377

-> test with 'GB'
GB tn, fp: 489, 4
GB fn, tp: 14, 1
GB f1 score: 0.100
GB cohens kappa score: 0.087

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 481, 10
LR fn, tp: 9, 4
LR f1 score: 0.296
LR cohens kappa score: 0.277
LR average precision score: 0.221

-> test with 'GB'
GB tn, fp: 488, 3
GB fn, tp: 12, 1
GB f1 score: 0.118
GB cohens kappa score: 0.107

-> test with 'KNN'
KNN tn, fp: 491, 0
KNN fn, tp: 13, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


====== 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 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 484, 9
LR fn, tp: 12, 3
LR f1 score: 0.222
LR cohens kappa score: 0.201
LR average precision score: 0.307

-> test with 'GB'
GB tn, fp: 491, 2
GB fn, tp: 13, 2
GB f1 score: 0.211
GB cohens kappa score: 0.201

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 487, 6
LR fn, tp: 13, 2
LR f1 score: 0.174
LR cohens kappa score: 0.157
LR average precision score: 0.270

-> test with 'GB'
GB tn, fp: 489, 4
GB fn, tp: 13, 2
GB f1 score: 0.190
GB cohens kappa score: 0.177

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 484, 9
LR fn, tp: 13, 2
LR f1 score: 0.154
LR cohens kappa score: 0.132
LR average precision score: 0.182

-> test with 'GB'
GB tn, fp: 492, 1
GB fn, tp: 15, 0
GB f1 score: 0.000
GB cohens kappa score: -0.004

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 482, 11
LR fn, tp: 13, 2
LR f1 score: 0.143
LR cohens kappa score: 0.119
LR average precision score: 0.240

-> test with 'GB'
GB tn, fp: 488, 5
GB fn, tp: 13, 2
GB f1 score: 0.182
GB cohens kappa score: 0.166

-> test with 'KNN'
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
Epoch 1/3
Epoch 2/3
Epoch 3/3
-> create 1912 synthetic samples
-> test with 'LR'
LR tn, fp: 483, 8
LR fn, tp: 10, 3
LR f1 score: 0.250
LR cohens kappa score: 0.232
LR average precision score: 0.249

-> test with 'GB'
GB tn, fp: 489, 2
GB fn, tp: 11, 2
GB f1 score: 0.235
GB cohens kappa score: 0.226

-> test with 'KNN'
KNN tn, fp: 491, 0
KNN fn, tp: 13, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 489, 15
LR fn, tp: 14, 7
LR f1 score: 0.483
LR cohens kappa score: 0.468
LR average precision score: 0.517


average:
LR tn, fp: 484.48, 8.12
LR fn, tp: 11.6, 3.0
LR f1 score: 0.230
LR cohens kappa score: 0.211
LR average precision score: 0.262


minimum:
LR tn, fp: 478, 4
LR fn, tp: 8, 0
LR f1 score: 0.000
LR cohens kappa score: -0.018
LR average precision score: 0.162


-----[ GB ]-----
maximum:
GB tn, fp: 492, 5
GB fn, tp: 15, 4
GB f1 score: 0.400
GB cohens kappa score: 0.391


average:
GB tn, fp: 490.0, 2.6
GB fn, tp: 13.12, 1.48
GB f1 score: 0.153
GB cohens kappa score: 0.143


minimum:
GB tn, fp: 488, 1
GB fn, tp: 10, 0
GB f1 score: 0.000
GB cohens kappa score: -0.010


-----[ KNN ]-----
maximum:
KNN tn, fp: 493, 0
KNN fn, tp: 15, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


average:
KNN tn, fp: 492.6, 0.0
KNN fn, tp: 14.6, 0.0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


minimum:
KNN tn, fp: 491, 0
KNN fn, tp: 13, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000