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***************************************************2022-02-26 02:54:24.562085*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %100.0
number of Augmented data:68
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 02:57:14.304453*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 44.44
The accuracy for ADABoost model is: %88.88888888888889
number of Augmented data:157
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %72.22222222222221
************************************************************************************************************************************
***************************************************2022-02-26 03:03:59.511680*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %100.0
number of Augmented data:68
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 03:04:26.154096*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 13.33
The accuracy for ADABoost model is: %93.33333333333333
number of Augmented data:68
Deep Dense model Accuracy is : 13.33
The accuracy for ADABoost model is: %93.33333333333333
************************************************************************************************************************************
***************************************************2022-02-26 03:07:03.219746*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 46.67
The accuracy for ADABoost model is: %100.0
number of Augmented data:68
Deep Dense model Accuracy is : 46.67
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 03:09:34.189836*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %100.0
number of Augmented data:157
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %94.44444444444444
************************************************************************************************************************************
***************************************************2022-02-26 03:15:33.723296*******************************************************
Data-sets:diabetes
Deep Dense model Accuracy is : 0.00
***************************************************2022-02-26 03:16:16.191027*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 40.00
The accuracy for ADABoost model is: %93.33333333333333
number of Augmented data:71
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %93.33333333333333
************************************************************************************************************************************
***************************************************2022-02-26 07:05:16.584286*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 33.33
The accuracy for ADABoost model is: %86.66666666666667
number of Augmented data:70
Deep Dense model Accuracy is : 53.33
The accuracy for ADABoost model is: %93.33333333333333
************************************************************************************************************************************
***************************************************2022-02-26 07:19:08.689973*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 44.44
The accuracy for ADABoost model is: %100.0
number of Augmented data:157
Deep Dense model Accuracy is : 44.44
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 07:34:37.534282*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %100.0
***************************************************2022-02-26 07:38:24.009198*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 46.67
The accuracy for ADABoost model is: %93.33333333333333
***************************************************2022-02-26 07:49:23.821792*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %93.33333333333333
***************************************************2022-02-26 07:55:54.455995*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %100.0
***************************************************2022-02-26 07:58:45.103931*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 40.00
The accuracy for ADABoost model is: %100.0
***************************************************2022-02-26 08:02:09.671605*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 40.00
The accuracy for ADABoost model is: %93.33333333333333
***************************************************2022-02-26 08:04:40.729424*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 46.67
The accuracy for ADABoost model is: %100.0
***************************************************2022-02-26 08:06:36.060243*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 33.33
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 53.33
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 08:16:13.116569*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 55.56
The accuracy for ADABoost model is: %88.88888888888889
number of Augmented data:633
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %77.77777777777779
************************************************************************************************************************************
***************************************************2022-02-26 08:26:32.091944*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 55.56
The accuracy for ADABoost model is: %88.88888888888889
number of Augmented data:633
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %77.77777777777779
************************************************************************************************************************************
***************************************************2022-02-26 08:29:06.544706*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 55.56
The accuracy for ADABoost model is: %88.88888888888889
number of Augmented data:633
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %77.77777777777779
************************************************************************************************************************************
***************************************************2022-02-26 08:32:54.804330*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 33.33
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 53.33
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 08:34:18.954568*******************************************************
Data-sets:soybean_csv.csv
***************************************************2022-02-26 08:37:33.995601*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 80.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:280
Deep Dense model Accuracy is : 60.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 08:45:09.731481*******************************************************
Data-sets:pima.csv
Deep Dense model Accuracy is : 62.34
The accuracy for ADABoost model is: %54.54545454545454
number of Augmented data:1944
Deep Dense model Accuracy is : 38.96
The accuracy for ADABoost model is: %66.23376623376623
************************************************************************************************************************************
***************************************************2022-02-26 13:12:59.726014*******************************************************
Data-sets:iris
Deep Dense model Accuracy is : 80.00
The accuracy for ADABoost model is: %93.33333333333333
number of Augmented data:71
***************************************************2022-02-26 13:14:21.024016*******************************************************
Data-sets:wine
Deep Dense model Accuracy is : 55.56
The accuracy for ADABoost model is: %100.0
number of Augmented data:632
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %88.88888888888889
************************************************************************************************************************************
***************************************************2022-02-26 13:27:13.127530*******************************************************
Data-sets: iris
Data-sets size: 150, 4
Deep Dense model Accuracy is : 73.33
The accuracy for ADABoost model is: %93.33333333333333
number of Augmented data:290
Deep Dense model Accuracy is : 46.67
The accuracy for ADABoost model is: %93.33333333333333
************************************************************************************************************************************
***************************************************2022-02-26 13:35:23.909530*******************************************************
Data-sets: wine
Data-sets size: 178, 13
Deep Dense model Accuracy is : 55.56
The accuracy for ADABoost model is: %100.0
number of Augmented data:632
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %88.88888888888889
************************************************************************************************************************************
***************************************************2022-02-26 14:01:35.408366*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 40.00
The accuracy for ADABoost model is: %86.66666666666667
number of Augmented data:287
Deep Dense model Accuracy is : 40.00
The accuracy for ADABoost model is: %86.66666666666667
************************************************************************************************************************************
***************************************************2022-02-26 14:18:44.961041*******************************************************
Data-sets: soybean_csv.csv
Data-sets size: 683,35
***************************************************2022-02-26 14:18:54.115039*******************************************************
Data-sets: Abalone.csv
Data-sets size: 4176,8
Deep Dense model Accuracy is : 38.52
The accuracy for ADABoost model is: %50.95693779904307
number of Augmented data:4542
Deep Dense model Accuracy is : 38.52
The accuracy for ADABoost model is: %53.110047846889955
************************************************************************************************************************************
***************************************************2022-02-26 22:12:52.950075*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %100.0
number of Augmented data:273
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-02-26 22:18:39.362908*******************************************************
Data-sets: seeds_dataset.txt
Data-sets size: 209,0
***************************************************2022-02-26 22:18:59.337908*******************************************************
***************************************************2022-02-26 22:21:02.206907*******************************************************
***************************************************2022-02-26 22:21:29.199913*******************************************************
***************************************************2022-02-26 22:22:22.714958*******************************************************
Data-sets: Wheat.csv
Data-sets size: 210,7
Deep Dense model Accuracy is : 33.33
The accuracy for ADABoost model is: %66.66666666666666
***************************************************2022-02-26 22:26:56.083880*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 66.67
***************************************************2022-02-26 22:26:58.721880*******************************************************
Data-sets: Acute.csv
Data-sets size: 120,7
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %100.0
***************************************************2022-02-26 22:27:30.677880*******************************************************
Data-sets: Breast Cancer Coimb.csv
Data-sets size: 116,9
Deep Dense model Accuracy is : 41.67
The accuracy for ADABoost model is: %75.0
***************************************************2022-02-26 22:28:29.947879*******************************************************
Data-sets: Immunotherapy.csv
Data-sets size: 90,7
Deep Dense model Accuracy is : 88.89
The accuracy for ADABoost model is: %88.88888888888889
number of Augmented data:310
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %77.77777777777779
************************************************************************************************************************************
***************************************************2022-02-26 22:37:33.339767*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 27.27
The accuracy for ADABoost model is: %40.909090909090914
***************************************************2022-02-26 22:38:12.413767*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 27.27
The accuracy for ADABoost model is: %40.909090909090914
***************************************************2022-02-26 22:40:07.438981*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 66.67
***************************************************2022-02-26 22:40:09.788980*******************************************************
Data-sets: wdbc_csv.csv
Data-sets size: 569,30
Deep Dense model Accuracy is : 47.37
The accuracy for ADABoost model is: %98.24561403508771
***************************************************2022-02-26 22:42:16.672981*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 33.33
The accuracy for ADABoost model is: %86.66666666666667
number of Augmented data:284
Deep Dense model Accuracy is : 33.33
The accuracy for ADABoost model is: %86.66666666666667
************************************************************************************************************************************
***************************************************2022-02-26 22:46:37.273981*******************************************************
Data-sets: waveform-5000_csv.csv
Data-sets size: 5000,40
Deep Dense model Accuracy is : 33.60
The accuracy for ADABoost model is: %83.0
***************************************************2022-02-26 22:55:31.492731*******************************************************
Data-sets: wdbc_csv.csv
Data-sets size: 569,30
Deep Dense model Accuracy is : 63.16
The accuracy for ADABoost model is: %98.24561403508771
***************************************************2022-02-26 23:01:17.594736*******************************************************
Data-sets: Acute.csv
Data-sets size: 120,7
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %100.0
***************************************************2022-02-26 23:02:04.319737*******************************************************
***************************************************2022-02-26 23:02:04.999736*******************************************************
Data-sets: Breast Cancer Coimb.csv
Data-sets size: 116,9
Deep Dense model Accuracy is : 75.00
The accuracy for ADABoost model is: %75.0
number of Augmented data:401
Deep Dense model Accuracy is : 75.00
The accuracy for ADABoost model is: %83.33333333333334
************************************************************************************************************************************
***************************************************2022-02-26 23:07:39.634737*******************************************************
***************************************************2022-02-26 23:07:40.255737*******************************************************
Data-sets: Cryotherapy.csv
Data-sets size: 91,6
***************************************************2022-02-26 23:08:45.753736*******************************************************
Data-sets: Cryotherapy.csv
Data-sets size: 86,6
Deep Dense model Accuracy is : 88.89
The accuracy for ADABoost model is: %100.0
number of Augmented data:286
Deep Dense model Accuracy is : 77.78
The accuracy for ADABoost model is: %77.77777777777779
************************************************************************************************************************************
***************************************************2022-02-26 23:13:01.728736*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 31.82
The accuracy for ADABoost model is: %45.45454545454545
***************************************************2022-02-26 23:13:43.500738*******************************************************
Data-sets: Immunotherapy.csv
Data-sets size: 90,7
Deep Dense model Accuracy is : 77.78
The accuracy for ADABoost model is: %77.77777777777779
number of Augmented data:314
Deep Dense model Accuracy is : 66.67
The accuracy for ADABoost model is: %77.77777777777779
************************************************************************************************************************************
***************************************************2022-02-26 23:18:55.652741*******************************************************
Data-sets: ionosphere_csv.csv
Data-sets size: 351,34
Deep Dense model Accuracy is : 91.67
The accuracy for ADABoost model is: %94.44444444444444
***************************************************2022-02-26 23:19:52.069737*******************************************************
Data-sets: ionosphere_csv.csv
Data-sets size: 351,34
Deep Dense model Accuracy is : 91.67
The accuracy for ADABoost model is: %94.44444444444444
***************************************************2022-02-26 23:20:13.629736*******************************************************
***************************************************2022-02-26 23:20:14.264736*******************************************************
***************************************************2022-02-26 23:20:47.740735*******************************************************
Data-sets: perfume_data.csv
Data-sets size: 19,28
***************************************************2022-02-26 23:21:13.420735*******************************************************
Data-sets: sonar_csv.csv
Data-sets size: 208,60
Deep Dense model Accuracy is : 76.19
The accuracy for ADABoost model is: %71.42857142857143
***************************************************2022-02-26 23:24:21.297736*******************************************************
Data-sets: waveform-5000_csv.csv
Data-sets size: 5000,40
Deep Dense model Accuracy is : 33.60
The accuracy for ADABoost model is: %83.0
***************************************************2022-02-26 23:27:44.044735*******************************************************
Data-sets: Wheat.csv
Data-sets size: 210,7
Deep Dense model Accuracy is : 38.10
The accuracy for ADABoost model is: %71.42857142857143
***************************************************2022-02-26 23:30:53.606736*******************************************************
***************************************************2022-03-05 11:06:46.447710*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %86.66666666666667
number of Augmented data:281
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %86.66666666666667
************************************************************************************************************************************
***************************************************2022-03-05 11:59:38.244100*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 31.82
The accuracy for ADABoost model is: %54.54545454545454
***************************************************2022-03-05 12:00:35.107099*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %86.66666666666667
number of Augmented data:281
Deep Dense model Accuracy is : 26.67
***************************************************2022-03-05 12:00:41.561100*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 31.82
The accuracy for ADABoost model is: %54.54545454545454
***************************************************2022-03-05 12:05:15.913100*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %86.66666666666667
number of Augmented data:281
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %86.66666666666667
************************************************************************************************************************************
***************************************************2022-03-05 12:05:53.516099*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %93.33333333333333
number of Augmented data:285
Deep Dense model Accuracy is : 26.67
The accuracy for ADABoost model is: %93.33333333333333
************************************************************************************************************************************
***************************************************2022-03-05 12:10:35.885100*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 36.36
The accuracy for ADABoost model is: %59.09090909090909
***************************************************2022-03-05 12:11:52.856098*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:12:23.363099*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:14:29.710098*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:16:06.249099*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:20:04.016100*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:21:58.025099*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:24:05.689099*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:24:43.728100*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:25:01.067099*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:28:12.416105*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:29:39.173100*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:40:06.179497*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:40:33.507496*******************************************************
Data-sets: ionosphere_csv.csv
Data-sets size: 351,34
***************************************************2022-03-05 12:42:38.280495*******************************************************
Data-sets: perfume_data.csv
Data-sets size: 19,28
***************************************************2022-03-05 12:43:05.429496*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:45:18.219496*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:46:14.312496*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
***************************************************2022-03-05 12:49:22.639494*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:51:25.917494*******************************************************
***************************************************2022-03-05 12:52:58.029496*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-05 12:55:53.620496*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 25.58
The accuracy for ADABoost model is: %32.55813953488372
***************************************************2022-03-05 12:59:45.983497*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:280
***************************************************2022-03-12 11:57:36.860607*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:284
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-03-12 12:09:53.324607*******************************************************
Data-sets: glass_csv.csv
Data-sets size: 214,9
Deep Dense model Accuracy is : 25.58
The accuracy for ADABoost model is: %32.55813953488372
***************************************************2022-03-12 12:12:01.022612*******************************************************
Data-sets: Immunotherapy.csv
Data-sets size: 90,7
Deep Dense model Accuracy is : 72.22
The accuracy for ADABoost model is: %77.77777777777779
number of Augmented data:277
Deep Dense model Accuracy is : 72.22
The accuracy for ADABoost model is: %72.22222222222221
************************************************************************************************************************************
***************************************************2022-03-12 12:25:52.178607*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-03-12 12:25:52.789606*******************************************************
Data-sets: ionosphere_csv.csv
Data-sets size: 351,34
Deep Dense model Accuracy is : 60.56
The accuracy for ADABoost model is: %90.14084507042254
***************************************************2022-03-12 12:30:23.540606*******************************************************
Data-sets: Cryotherapy.csv
Data-sets size: 86,6
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %100.0
number of Augmented data:252
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-03-12 12:35:24.979611*******************************************************
Data-sets: waveform-5000_csv.csv
Data-sets size: 5000,40
Deep Dense model Accuracy is : 31.50
The accuracy for ADABoost model is: %85.1
***************************************************2022-03-12 13:03:07.453607*******************************************************
Data-sets: Acute.csv
Data-sets size: 120,7
Deep Dense model Accuracy is : 37.50
The accuracy for ADABoost model is: %100.0
***************************************************2022-03-12 13:04:56.347611*******************************************************
Data-sets: wdbc_csv.csv
Data-sets size: 569,30
Deep Dense model Accuracy is : 62.28
The accuracy for ADABoost model is: %97.36842105263158
***************************************************2022-03-12 13:14:02.411608*******************************************************
Data-sets: Breast Cancer Coimb.csv
Data-sets size: 116,9
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %79.16666666666666
number of Augmented data:360
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %79.16666666666666
************************************************************************************************************************************
***************************************************2022-03-12 13:22:02.506123*******************************************************
Data-sets: Breast Cancer Coimb.csv
Data-sets size: 116,9
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %79.16666666666666
number of Augmented data:360
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %79.16666666666666
************************************************************************************************************************************
***************************************************2022-03-12 13:24:46.274123*******************************************************
Data-sets: wine
Data-sets size: 178,13
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:557
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %88.88888888888889
************************************************************************************************************************************
***************************************************2022-03-12 13:49:27.292123*******************************************************
Data-sets: diabetes
Data-sets size: 442,10
Deep Dense model Accuracy is : 0.00
***************************************************2022-05-06 06:08:00.386627*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:277
***************************************************2022-05-06 06:19:46.876628*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-05-06 06:30:36.785626*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 100.00
***************************************************2022-05-06 06:35:29.813627*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-05-06 06:35:31.575627*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 100.00
***************************************************2022-05-06 06:43:30.252627*******************************************************
***************************************************2022-05-06 06:43:30.368628*******************************************************
Data-sets: iris
Data-sets size: 150,4
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-05-06 06:51:10.265626*******************************************************
Data-sets: iris
Data-sets size: 150,4
***************************************************2022-05-06 06:51:10.397627*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 50.00
Deep Dense model Accuracy is : 56.67
***************************************************2022-05-06 06:59:59.977627*******************************************************
***************************************************2022-05-06 07:00:00.136626*******************************************************
Data-sets: iris
Data-sets size: 150,4
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 40.00
***************************************************2022-05-06 07:04:39.244631*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 50.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:272
***************************************************2022-05-06 07:07:54.327627*******************************************************
Data-sets: iris
Data-sets size: 150,4
Deep Dense model Accuracy is : 63.33
The accuracy for ADABoost model is: %100.0
number of Augmented data:277
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 07:11:08.130626*******************************************************
Data-sets: wine
Data-sets size: 178,13
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:557
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %91.66666666666666
************************************************************************************************************************************
***************************************************2022-05-06 07:22:26.049632*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 50
Deep Dense model Accuracy is : 83.33
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:553
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %94.44444444444444
************************************************************************************************************************************
***************************************************2022-05-06 07:26:38.772627*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 50
Deep Dense model Accuracy is : 83.33
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:553
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %94.44444444444444
************************************************************************************************************************************
***************************************************2022-05-06 07:30:33.421626*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 50
Deep Dense model Accuracy is : 83.33
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:553
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %94.44444444444444
************************************************************************************************************************************
***************************************************2022-05-06 07:33:02.083629*******************************************************
Data-sets: diabetes
Data-sets size: 442,10
Number of EPOC: 50
***************************************************2022-05-06 07:35:20.951627*******************************************************
Data-sets: diabetes
Data-sets size: 442,10
Number of EPOC: 50
***************************************************2022-05-06 07:36:49.406627*******************************************************
***************************************************2022-05-06 07:37:13.936627*******************************************************
Data-sets: linnerud
Data-sets size: 20,3
Number of EPOC: 50
***************************************************2022-05-06 08:44:17.011244*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 50
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 96.67
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 09:12:08.948143*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 50
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 96.67
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 09:13:11.759144*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 150
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:555
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %83.33333333333334
************************************************************************************************************************************
***************************************************2022-05-06 09:20:34.029143*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 150
Deep Dense model Accuracy is : 93.33
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 09:23:38.380762*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 150
Deep Dense model Accuracy is : 93.33
***************************************************2022-05-06 09:23:40.531763*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 150
Deep Dense model Accuracy is : 93.33
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 09:26:55.493764*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 10
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:555
Deep Dense model Accuracy is : 69.44
The accuracy for ADABoost model is: %83.33333333333334
************************************************************************************************************************************
***************************************************2022-05-06 09:32:09.080762*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 10
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:275
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 09:36:17.666763*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 10
Deep Dense model Accuracy is : 38.89
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:555
Deep Dense model Accuracy is : 69.44
The accuracy for ADABoost model is: %83.33333333333334
***************************************************2022-05-06 09:39:33.243764*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 10
Deep Dense model Accuracy is : 63.33
The accuracy for ADABoost model is: %100.0
number of Augmented data:279
Deep Dense model Accuracy is : 30.00
The accuracy for ADABoost model is: %100.0
************************************************************************************************************************************
***************************************************2022-05-06 09:42:26.683768*******************************************************
Data-sets: iris
Data-sets size: 150,4
Number of EPOC: 400
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %100.0
number of Augmented data:276
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %96.66666666666667
*****************************************************************************************************************************************
***************************************************2022-05-06 10:21:40.867762*******************************************************
Data-sets: wine
Data-sets size: 178,13
Number of EPOC: 400
*********Model Summary***********Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 256) 3584
batch_normalization (BatchN (None, 256) 1024
ormalization)
dropout (Dropout) (None, 256) 0
dense_1 (Dense) (None, 256) 65792
batch_normalization_1 (Batc (None, 256) 1024
hNormalization)
dropout_1 (Dropout) (None, 256) 0
dense_2 (Dense) (None, 512) 131584
batch_normalization_2 (Batc (None, 512) 2048
hNormalization)
dropout_2 (Dropout) (None, 512) 0
dense_3 (Dense) (None, 3) 1539
=================================================================
Total params: 206,595
Trainable params: 204,547
Non-trainable params: 2,048
_________________________________________________________________
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %91.66666666666666
number of Augmented data:552
*********Model Summary***********Model: "sequential_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_4 (Dense) (None, 256) 3584
batch_normalization_3 (Batc (None, 256) 1024
hNormalization)
dropout_3 (Dropout) (None, 256) 0
dense_5 (Dense) (None, 256) 65792
batch_normalization_4 (Batc (None, 256) 1024
hNormalization)
dropout_4 (Dropout) (None, 256) 0
dense_6 (Dense) (None, 512) 131584
batch_normalization_5 (Batc (None, 512) 2048
hNormalization)
dropout_5 (Dropout) (None, 512) 0
dense_7 (Dense) (None, 3) 1539
=================================================================
Total params: 206,595
Trainable params: 204,547
Non-trainable params: 2,048
_________________________________________________________________
Deep Dense model Accuracy is : 100.00
The accuracy for ADABoost model is: %94.44444444444444
************************************************************************************************************************************
***************************************************2022-05-07 22:06:13.011729*******************************************************
Data-sets: breast_cancer
Data-sets size: 569,30
Number of EPOC: 10
********************Model Summary******************
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 256) 7936
batch_normalization (BatchN (None, 256) 1024
ormalization)
dropout (Dropout) (None, 256) 0
dense_1 (Dense) (None, 256) 65792
batch_normalization_1 (Batc (None, 256) 1024
hNormalization)
dropout_1 (Dropout) (None, 256) 0
dense_2 (Dense) (None, 512) 131584
batch_normalization_2 (Batc (None, 512) 2048
hNormalization)
dropout_2 (Dropout) (None, 512) 0
dense_3 (Dense) (None, 2) 1026
=================================================================
Total params: 210,434
Trainable params: 208,386
Non-trainable params: 2,048
_________________________________________________________________
Deep Dense model Accuracy is : 92.98
The accuracy for ADABoost model is: %97.36842105263158
***************************************************2022-05-07 22:11:50.464729*******************************************************
Data-sets: breast_cancer
Data-sets size: 569,30
Number of EPOC: 10
********************Model Summary******************
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 256) 7936
batch_normalization (BatchN (None, 256) 1024
ormalization)
dropout (Dropout) (None, 256) 0
dense_1 (Dense) (None, 256) 65792
batch_normalization_1 (Batc (None, 256) 1024
hNormalization)
dropout_1 (Dropout) (None, 256) 0
dense_2 (Dense) (None, 512) 131584
batch_normalization_2 (Batc (None, 512) 2048
hNormalization)
dropout_2 (Dropout) (None, 512) 0
dense_3 (Dense) (None, 2) 1026
=================================================================
Total params: 210,434
Trainable params: 208,386
Non-trainable params: 2,048
_________________________________________________________________
Deep Dense model Accuracy is : 84.21
The accuracy for ADABoost model is: %97.36842105263158
***************************************************2022-05-07 22:18:47.273729*******************************************************
Data-sets: breast_cancer
Data-sets size: 569,30
Number of EPOC: 100
********************Model Summary******************
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 256) 7936
batch_normalization (BatchN (None, 256) 1024
ormalization)
dropout (Dropout) (None, 256) 0
dense_1 (Dense) (None, 256) 65792
batch_normalization_1 (Batc (None, 256) 1024
hNormalization)
dropout_1 (Dropout) (None, 256) 0
dense_2 (Dense) (None, 512) 131584
batch_normalization_2 (Batc (None, 512) 2048
hNormalization)
dropout_2 (Dropout) (None, 512) 0
dense_3 (Dense) (None, 2) 1026
=================================================================
Total params: 210,434
Trainable params: 208,386
Non-trainable params: 2,048
_________________________________________________________________
Deep Dense model Accuracy is : 96.49
The accuracy for ADABoost model is: %97.36842105263158
***************************************************2022-05-07 22:28:08.698729*******************************************************
Data-sets: breast_cancer
Data-sets size: 569,30
Number of EPOC: 150
********************Model Summary******************
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 256) 7936
batch_normalization (BatchN (None, 256) 1024
ormalization)
dropout (Dropout) (None, 256) 0
dense_1 (Dense) (None, 256) 65792
batch_normalization_1 (Batc (None, 256) 1024
hNormalization)
dropout_1 (Dropout) (None, 256) 0
dense_2 (Dense) (None, 512) 131584
batch_normalization_2 (Batc (None, 512) 2048