Complete results and additional material for the article “PCTBagging: From Inner Ensembles to Ensembles. A trade-off between Discriminating Capacity and Interpretability”

2021-12-01

 

This page contains the full tables related to the work presented in the article:

Igor Ibarguren, Jesús M. Pérez, Javier Muguerza, Olatz Arbelaitz and Ainhoa Yera.  
        "PCTBagging: From Inner Ensembles to Ensembles. A trade-off between Discriminating Capacity and Interpretabibility". Information Sciences (2022), Vol. 583, pp 219-238.

First, we present the table with the characteristics for the 96 datasets used in this study, divided into three contexts.

Then, for each of the evaluation measures, we include the full tables of the results related to the different proposed consolidation percentages of PCTBagging, Bagging, CTC and C4.5.

 

All the tables of results can be downloaded as an Excel document or as a CSV file.

 

Content

1. Datasets characteristics. 1

2  Subsample numbers by data set to achieve the selected coverage value. 4

3. Results for the discriminating capacity, structural complexity, and computational cost measures. 6

 

Index of Tables

Table 1. Description of standard datasets. 2

Table 2. Description of imbalanced datasets. 2

Table 3. Subsample numbers for standard data sets. 4

Table 4:Subsample amounts for imbalanced data sets. 5

Table 5. AUC values for all algorithms over 96 datasets. 6

Table 6. Number of Internal Nodes values for all algorithms over 96 datasets. 8

Table 7. Time values for all algorithms over 96 datasets. 11

 

1. Datasets characteristics

This section contains the tables with the characteristics for the 96 datasets from the KEEL repository used in this study. First we present the datasets from the first (Standard) context and then from the second (Imbalanced) context. SMOTE-preprocessed datasets have the same characteristics as the datasets from Table 2, but the minority class oversampled until it has the majority class’ size.

 


Table 1. Description of standard datasets.

Data set

#Ants

#Examples

#Classes

%min

%maj

Size Of Min. Class

Size of Maj. Class

lymphography

18

148

4

1.36%

54.73%

2

81

ecoli

7

336

8

0.6%

42.56%

2

143

car

6

1728

4

3.77%

70.03%

65

1210

nursery

8

1296

5

0.08%

33.34%

1

432

cleveland

13

297

5

4.38%

53.88%

13

160

zoo

17

101

7

3.97%

40.6%

4

41

glass

9

214

6

4.21%

35.52%

9

76

flare

10

1066

6

4.04%

31.06%

43

331

abalone

8

418

22

0.24%

16.51%

1

69

balance

4

625

3

7.84%

46.08%

49

288

dermatology

33

358

6

5.59%

31.01%

20

111

hepatitis

19

80

2

16.25%

83.75%

13

67

newthyroid

5

215

3

13.96%

69.77%

30

150

haberman

3

306

2

26.48%

73.53%

81

225

breast

9

277

2

29.25%

70.76%

81

196

german

20

1000

2

30%

70%

300

700

wisconsin

9

630

2

34.61%

65.4%

218

412

contraceptive

9

1473

3

22.61%

42.71%

333

629

 

tictactoe

9

958

2

34.66%

65.35%

332

626

pima

8

768

2

34.9%

65.11%

268

500

magic

10

1902

2

35.13%

64.88%

668

1234

wine

13

178

3

26.97%

39.89%

48

71

bupa

6

345

2

42.03%

57.98%

145

200

heart

13

270

2

44.45%

55.56%

120

150

australian

14

690

2

44.5%

55.51%

307

383

crx

15

653

2

45.33%

54.68%

296

357

vehicle

18

846

4

23.53%

25.77%

199

218

penbased

16

1100

10

9.55%

10.46%

105

115

ring

20

740

2

49.6%

50.41%

367

373

iris

4

150

3

33.34%

33.34%

50

50

Mean

11.77

638.93

4.27

21%

50%

139

319.93

Median

9.5

521.5

3

23%

54%

73

209

 

 

Table 2. Description of imbalanced datasets.

Data set

#Atts.

#Examples

Imbalance

Size Of Min. Class

Size of Maj. Class

Abalone19

8

4174

0.77%

32

4142

Yeast6

8

1484

2.49%

37

1447

Yeast5

8

1484

2.96%

44

1440

Yeast4

8

1484

3.43%

51

1433

Yeast2vs8

8

482

4.15%

20

462

Glass5

9

214

4.2%

9

205

Abalone9vs18

8

731

5.65%

41

690

Glass4

9

214

6.07%

13

201

Ecoli4

7

336

6.74%

23

313

Glass2

9

214

8.78%

19

195

Vowel0

13

988

9.01%

89

899

Page-blocks0

10

5472

10.23%

560

4912

Ecoli3

7

336

10.88%

37

299

Yeast3

8

1484

10.98%

163

1321

Glass6

9

214

13.55%

29

185

Segment0

19

2308

14.26%

329

1979

Ecoli2

7

336

15.48%

52

284

New-thyroid1

5

215

16.28%

35

180

New-thyroid2

5

215

16.89%

36

179

Ecoli1

7

336

22.92%

77

259

Vehicle0

18

846

23.64%

200

646

Glass0123vs456

9

214

23.83%

51

163

Haberman

3

306

27.42%

84

222

Vehicle1

18

846

28.37%

240

606

Vehicle2

18

846

28.37%

240

606

Vehicle3

18

846

28.37%

240

606

Yeast1

8

1484

28.91%

429

1055

Glass0

9

214

32.71%

70

144

Iris0

4

150

33.33%

50

100

Pima

8

768

34.84%

268

500

Ecoli0vs1

7

220

35%

77

143

Wisconsin

9

683

35%

239

444

Glass1

9

214

35.51%

76

138

Mean

9.39

919.94

17.61%

120

799.94

Median

8

482

15.48%

52

444

 


 

2  Subsample numbers by data set to achieve the selected coverage value

The tables in this section show the number of subsamples computed for each data set for 99% coverage value. Table 3 refers to standard data sets and Table 4 refers to imbalanced data sets.

For imbalanced data sets preprocessed with SMOTE, only the total example number and the size of the minority class change from the data sets without the preprocessing. In these data sets the minority class has been oversampled with SMOTE until it has the same size as the majority class.

 

Table 3. Subsample numbers for standard data sets.

Original

Training sample

Subsample set

 

Data set

Size

#Class

%Min

Size

Min.

Class

Size

Maj. Class Size

Size

Number

lymphography

148

4

1.36%

119

2

66

12

99

 

ecoli

336

8

0.6%

269

2

115

48

86

 

car

1728

4

3.77%

1383

53

969

212

82

 

nursery

1296

5

0.08%

1037

1

346

105

74

 

cleveland

297

5

4.38%

238

11

129

55

52

 

zoo

101

7

3.97%

81

4

33

28

36

 

glass

214

6

4.21%

172

8

62

48

34

 

flare

1066

6

4.04%

853

35

265

210

33

 

abalone

418

22

0.24%

335

1

56

154

35

 

balance

625

3

7.84%

500

40

231

120

25

 

dermatology

358

6

5.59%

287

17

89

102

22

 

hepatitis

80

2

16.25%

64

11

54

22

21

 

newthyroid

215

3

13.96%

172

24

120

72

21

 

haberman

306

2

26.48%

245

65

181

130

11

 

breast

277

2

29.25%

222

65

158

130

9

 

german

1000

2

30%

800

240

560

480

9

 

wisconsin

630

2

34.61%

504

175

330

350

7

 

contraceptive

1473

3

22.61%

1179

267

504

801

7

 

tictactoe

958

2

34.66%

767

266

502

532

7

 

pima

768

2

34.9%

615

215

401

430

6

 

magic

1902

2

35.13%

1522

535

988

1070

6

 

wine

178

3

26.97%

143

39

58

117

5

 

bupa

345

2

42.03%

276

116

160

232

4

 

heart

270

2

44.45%

216

96

120

192

3

 

australian

690

2

44.5%

552

246

307

492

3

 

crx

653

2

45.33%

523

238

286

476

3

 

vehicle

846

4

23.53%

677

160

175

640

3

 

penbased

1100

10

9.55%

880

84

92

840

3

 

ring

740

2

49.6%

592

294

299

588

3

 

iris[1]

150

3

33.34%

120

40

40

66

6

 

 Mean

638.94

4.27

22%

511.44

111.67

256.54

291.8

24

 

Median

521.5

3

23.07%

417.5

59

167.5

173

9

 

 

Table 4:Subsample amounts for imbalanced data sets

Original

Training sample

Subsample set

Data set

Size

%Min

Size

Min.

Class

Size

Maj. Class Size

Size

Number

Abalone19

4174

0.77

3340

26

3314

52

585

Yeast6

1484

2.49

1188

30

1158

60

176

Yeast5

1484

2.96

1189

36

1153

72

146

Yeast4

1484

3.43

1188

41

1147

82

127

Yeast2vs8

482

4.15

387

17

370

34

98

Glass5

214

4.2

173

8

165

16

93

Abalone9vs18

731

5.65

586

34

552

68

73

Glass4

214

6.07

172

11

161

22

66

Ecoli4

336

6.74

270

19

251

38

59

Glass2

214

8.78

173

16

157

32

43

Vowel0

988

9.01

792

72

720

144

44

Page-blocks0

5472

10.23

4378

448

3930

896

39

Ecoli3

336

10.88

270

30

240

60

35

Yeast3

1484

10.98

1188

131

1057

262

35

Glass6

214

13.55

173

24

149

48

27

Segment0

2308

14.26

1848

264

1584

528

26

Ecoli2

336

15.48

270

42

228

84

23

New-thyroid1

215

16.28

173

29

144

58

21

New-thyroid2

215

16.89

173

30

143

60

20

Ecoli1

336

22.92

270

62

208

124

14

Vehicle0

846

23.64

677

160

517

320

13

Glass0123vs456

214

23.83

172

41

131

82

13

Haberman

306

27.42

246

68

178

136

10

Vehicle1

846

28.37

678

193

485

386

10

Vehicle2

846

28.37

678

193

485

386

10

Vehicle3

846

28.37

678

193

485

386

10

Yeast1

1484

28.91

1188

344

844

688

9

Glass0

214

32.71

172

56

116

112

7

Iris0

150

33.33

121

40

81

80

7

Pima

768

34.84

616

215

401

430

6

Ecoli0vs1

220

35

177

62

115

124

6

Wisconsin

683

35

548

192

356

384

6

Glass1

214

35.51

172

61

111

122

6

 Mean

919.94

17.61

737.09

96.61

640.48

193.21

56

Median

482

15.48

387

42

356

84

23

 

3. Results for the discriminating capacity, structural complexity, and computational cost measures.

This section includes the full tables of the results related to the algorithms compared in the study (PCTBagging with 11 consolidation percentages, Bagging, CTC, and C4.5) for the three performance metrics used in the study: AUC, Number of Internal Nodes, and Time. Numbers in bold indicate the best value for that particular dataset. In these tables we have treated C4.5 as reference for all algorithms. Cells with gray background indicate algorithms performing better than C4.5.

 

3.1 Results for the AUC measure

 

Table 5. AUC values for all algorithms over 96 datasets.

CTC

PCTBagging

Bagging

C4.5

 

 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

 

 

1.Standard lymphography

.7755

.8032

.7998

.7941

.7984

.8049

.8260

.8282

.8547

.8598

.8640

.8646

.8646

.8193

1.Standard ecoli

.8942

.8884

.8894

.8903

.8935

.8985

.9057

.9066

.9119

.9198

.9391

.9392

.9392

.8780

1.Standard car

.9468

.9450

.9472

.9452

.9421

.9388

.9358

.9339

.9307

.9343

.9366

.9459

.9459

.9681

1.Standard nursery

.9646

.9570

.9559

.9544

.9519

.9498

.9479

.9457

.9431

.9446

.9464

.9455

.9455

.9610

1.Standard cleveland

.6668

.6919

.6987

.7047

.7112

.7229

.7353

.7395

.7500

.7571

.7646

.7909

.7909

.6604

1.Standard zoo

.9683

.9536

.9532

.9579

.9653

.9749

.9746

.9743

.9736

.9810

.9834

.9879

.9879

.9814

1.Standard glass

.8111

.8195

.8197

.8220

.8333

.8430

.8484

.8479

.8582

.8664

.8718

.8825

.8825

.8230

1.Standard flare

.9184

.9045

.9050

.9055

.9061

.9075

.9085

.9103

.9122

.9128

.9130

.9130

.9130

.9154

1.Standard abalone

.6258

.6117

.6108

.6110

.6130

.6187

.6267

.6373

.6420

.6481

.6721

.6813

.6813

.5668

1.Standard balance

.8501

.8789

.8817

.8844

.8870

.8898

.8961

.9033

.9133

.9207

.9245

.9434

.9434

.8359

1.Standard dermatology

.9771

.9674

.9682

.9701

.9723

.9751

.9777

.9790

.9819

.9867

.9898

.9949

.9949

.9572

1.Standard hepatitis

.6692

.7452

.7519

.7481

.7657

.7629

.7780

.7805

.7906

.8022

.8654

.8761

.8761

.4690

1.Standard newthyroid

.9466

.9541

.9559

.9571

.9610

.9634

.9667

.9688

.9741

.9784

.9782

.9878

.9878

.9331

1.Standard haberman

.5455

.6368

.6387

.6468

.6493

.6566

.6603

.6703

.6714

.6769

.6785

.6895

.6895

.5714

1.Standard breast

.5858

.6254

.6176

.6425

.6361

.6415

.6500

.6512

.6606

.6683

.6859

.6885

.6885

.6016

1.Standard german

.6692

.6925

.6994

.7053

.7114

.7151

.7237

.7366

.7501

.7521

.7576

.7646

.7646

.6643

1.Standard wisconsin

.9362

.9497

.9536

.9525

.9562

.9564

.9647

.9644

.9658

.9697

.9795

.9800

.9800

.9323

1.Standard contraceptive

.6697

.6590

.6627

.6657

.6704

.6740

.6796

.6838

.6912

.7028

.7128

.7231

.7231

.6683

1.Standard tictactoe

.8906

.9004

.9042

.9058

.9067

.9086

.9120

.9251

.9322

.9386

.9482

.9754

.9754

.9002

1.Standard pima

.7080

.6958

.7094

.7195

.7289

.7422

.7559

.7663

.7748

.7910

.8076

.8229

.8229

.7529

1.Standard magic

.7499

.7502

.7603

.7675

.7753

.7838

.7948

.8031

.8114

.8224

.8377

.8633

.8633

.7655

1.Standard wine

.9549

.9680

.9688

.9712

.9749

.9828

.9844

.9844

.9925

.9925

.9955

.9955

.9955

.9609

1.Standard bupa

.6561

.6736

.6754

.6756

.6787

.6851

.6907

.6961

.6917

.7026

.7218

.7469

.7469

.6897

1.Standard heart

.7787

.8042

.8094

.8122

.8111

.8183

.8219

.8231

.8262

.8346

.8587

.8603

.8603

.8021

1.Standard australian

.8695

.8663

.8705

.8754

.8831

.8922

.9001

.9062

.9073

.9136

.9187

.9206

.9206

.8578

1.Standard crx

.8718

.8843

.8882

.8923

.8950

.8989

.9018

.9031

.9089

.9177

.9233

.9267

.9267

.8664

1.Standard vehicle

.8453

.8346

.8391

.8477

.8567

.8666

.8736

.8859

.8967

.9097

.9201

.9279

.9279

.8462

1.Standard penbased

.9519

.9429

.9453

.9487

.9513

.9556

.9597

.9647

.9686

.9760

.9816

.9944

.9944

.9523

1.Standard ring

.8544

.8540

.8578

.8630

.8742

.8840

.8887

.8935

.9084

.9209

.9311

.9377

.9377

.8489

1.Standard iris

.9681

.9621

.9619

.9683

.9688

.9687

.9825

.9825

.9851

.9851

.9854

.9854

.9854

.9538

2.Imbalanced abalone19

.5000

.7616

.7616

.7616

.7616

.7616

.7616

.7616

.7616

.7616

.7616

.7616

.7616

.5000

2.Imbalanced yeast6

.7816

.9241

.9243

.9242

.9244

.9251

.9253

.9257

.9257

.9254

.9269

.9336

.9336

.7855

2.Imbalanced yeast5

.9671

.9865

.9864

.9865

.9865

.9870

.9880

.9884

.9891

.9899

.9918

.9916

.9916

.9584

2.Imbalanced yeast4

.7278

.9222

.9223

.9217

.9221

.9218

.9223

.9225

.9253

.9264

.9293

.9304

.9304

.7799

2.Imbalanced yeast-2_vs_8

.7739

.8618

.8618

.8618

.8618

.8618

.8601

.8601

.8601

.8601

.8601

.8601

.8601

.5718

2.Imbalanced glass5

.9800

.9895

.9895

.9895

.9895

.9895

.9893

.9893

.9893

.9890

.9876

.9876

.9876

.9951

2.Imbalanced abalone9-18

.5283

.8617

.8615

.8615

.8614

.8617

.8618

.8618

.8617

.8617

.8633

.8616

.8616

.6547

2.Imbalanced glass4

.8525

.9195

.9195

.9235

.9235

.9260

.9293

.9293

.9280

.9280

.9447

.9447

.9447

.6925

2.Imbalanced ecoli4

.8132

.9074

.9074

.9074

.9155

.9157

.9174

.9174

.9176

.9458

.9694

.9694

.9694

.7643

2.Imbalanced glass2

.5552

.8451

.8411

.8407

.8409

.8402

.8512

.8495

.8483

.8461

.8464

.8461

.8461

.7535

2.Imbalanced vowel0

.9500

.9634

.9638

.9641

.9644

.9648

.9660

.9665

.9684

.9692

.9784

.9826

.9826

.9706

2.Imbalanced page-blocks0

.9362

.9775

.9776

.9779

.9781

.9782

.9788

.9804

.9814

.9836

.9853

.9893

.9893

.9595

2.Imbalanced ecoli3

.8887

.9241

.9258

.9264

.9281

.9289

.9309

.9307

.9373

.9408

.9411

.9390

.9390

.7638

2.Imbalanced yeast3

.8826

.9578

.9578

.9583

.9592

.9596

.9599

.9598

.9629

.9636

.9645

.9702

.9702

.9054

2.Imbalanced glass6

.8352

.9365

.9365

.9365

.9440

.9438

.9461

.9461

.9440

.9523

.9495

.9495

.9495

.7914

2.Imbalanced segment0

.9895

.9946

.9947

.9949

.9952

.9960

.9964

.9967

.9969

.9970

.9969

.9977

.9977

.9844

2.Imbalanced ecoli2

.8711

.9137

.9148

.9162

.9177

.9174

.9193

.9207

.9225

.9294

.9332

.9382

.9382

.8459

2.Imbalanced new-thyroid1

.9638

.9630

.9630

.9629

.9660

.9671

.9690

.9690

.9710

.9926

.9935

.9935

.9935

.9655

2.Imbalanced new-thyroid2

.9650

.9672

.9672

.9672

.9691

.9680

.9676

.9676

.9704

.9873

.9885

.9885

.9885

.9472

2.Imbalanced ecoli1

.8768

.9346

.9338

.9350

.9365

.9380

.9415

.9445

.9458

.9474

.9473

.9525

.9525

.8807

2.Imbalanced vehicle0

.9460

.9665

.9667

.9681

.9734

.9749

.9792

.9801

.9827

.9838

.9838

.9886

.9886

.9468

2.Imbalanced glass-0-1-2-3_vs_4-5-6

.8743

.9313

.9319

.9312

.9315

.9317

.9380

.9409

.9421

.9552

.9655

.9721

.9721

.9209

2.Imbalanced haberman

.5674

.6364

.6395

.6408

.6432

.6449

.6463

.6527

.6559

.6592

.6635

.6814

.6814

.5714

2.Imbalanced vehicle1

.6900

.7762

.7764

.7783

.7827

.7876

.7951

.8007

.8054

.8064

.8143

.8414

.8414

.7099

2.Imbalanced vehicle2

.9521

.9600

.9618

.9659

.9678

.9727

.9767

.9817

.9854

.9896

.9929

.9946

.9946

.9398

2.Imbalanced vehicle3

.7224

.7855

.7863

.7878

.7891

.7950

.8024

.8074

.8174

.8313

.8401

.8563

.8563

.7357

2.Imbalanced yeast1

.7144

.7310

.7314

.7342

.7373

.7411

.7456

.7515

.7593

.7656

.7742

.7889

.7889

.7017

2.Imbalanced glass0

.8020

.8562

.8566

.8591

.8582

.8625

.8705

.8715

.8782

.8899

.8982

.9002

.9002

.8119

2.Imbalanced iris0

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

2.Imbalanced pima

.7088

.7170

.7177

.7213

.7249

.7323

.7455

.7611

.7748

.7867

.8000

.8180

.8180

.7529

2.Imbalanced ecoli-0_vs_1

.9816

.9825

.9825

.9825

.9825

.9825

.9838

.9838

.9838

.9838

.9838

.9838

.9838

.9832

2.Imbalanced wisconsin

.9711

.9643

.9643

.9661

.9659

.9672

.9714

.9714

.9729

.9751

.9798

.9798

.9798

.9700

2.Imbalanced glass1

.7260

.7374

.7449

.7527

.7506

.7557

.7607

.7673

.7765

.7852

.8014

.8240

.8240

.7192

3.Imb-SMOTE abalone19

.6469

.6909

.6910

.6900

.6875

.6890

.6909

.6994

.7079

.7145

.7175

.7671

.7671

.5363

3.Imb-SMOTE yeast6

.8713

.9001

.9021

.9014

.9025

.9045

.9062

.9062

.9060

.9088

.9116

.9384

.9384

.8490

3.Imb-SMOTE yeast5

.9718

.9821

.9821

.9819

.9817

.9824

.9827

.9829

.9839

.9842

.9915

.9909

.9909

.9646

3.Imb-SMOTE yeast4

.8298

.8896

.8893

.8906

.8940

.8966

.9045

.9141

.9189

.9209

.9232

.9255

.9255

.8107

3.Imb-SMOTE yeast-2_vs_8

.8549

.8592

.8539

.8517

.8559

.8526

.8512

.8533

.8544

.8566

.8536

.8528

.8528

.7259

3.Imb-SMOTE glass5

.9654

.9793

.9793

.9812

.9817

.9824

.9890

.9888

.9883

.9883

.9841

.9849

.9849

.8890

3.Imb-SMOTE abalone9-18

.6750

.6961

.6949

.6955

.6974

.7014

.7088

.7157

.7256

.7360

.7441

.8018

.8018

.6579

3.Imb-SMOTE glass4

.8857

.9183

.9195

.9192

.9267

.9287

.9330

.9342

.9424

.9425

.9584

.9617

.9617

.8621

3.Imb-SMOTE ecoli4

.9053

.9369

.9343

.9350

.9351

.9361

.9400

.9471

.9599

.9639

.9694

.9740

.9740

.7783

3.Imb-SMOTE glass2

.8073

.8254

.8215

.8179

.8186

.8235

.8225

.8315

.8413

.8301

.8227

.8252

.8252

.7325

3.Imb-SMOTE vowel0

.9549

.9756

.9754

.9752

.9759

.9760

.9765

.9816

.9888

.9897

.9919

.9851

.9851

.9523

3.Imb-SMOTE page-blocks0

.9780

.9810

.9815

.9817

.9818

.9822

.9839

.9847

.9855

.9868

.9889

.9900

.9900

.9582

3.Imb-SMOTE ecoli3

.8901

.9163

.9161

.9160

.9164

.9233

.9291

.9299

.9322

.9347

.9375

.9344

.9344

.7989

3.Imb-SMOTE yeast3

.9455

.9593

.9596

.9600

.9609

.9624

.9639

.9650

.9657

.9680

.9708

.9714

.9714

.9158

3.Imb-SMOTE glass6

.8538

.9257

.9217

.9221

.9260

.9265

.9377

.9423

.9440

.9427

.9435

.9456

.9456

.8908

3.Imb-SMOTE segment0

.9932

.9931

.9932

.9933

.9933

.9934

.9940

.9946

.9949

.9950

.9957

.9978

.9978

.9941

3.Imb-SMOTE ecoli2

.8618

.9075

.9082

.9076

.9083

.9076

.9055

.9098

.9112

.9175

.9296

.9411

.9411

.8768

3.Imb-SMOTE new-thyroid1

.9580

.9702

.9701

.9721

.9733

.9733

.9748

.9753

.9763

.9820

.9953

.9955

.9955

.9802

3.Imb-SMOTE new-thyroid2

.9677

.9688

.9688

.9671

.9671

.9713

.9794

.9871

.9886

.9894

.9902

.9917

.9917

.9714

3.Imb-SMOTE ecoli1

.9029

.9408

.9444

.9450

.9454

.9458

.9468

.9486

.9523

.9542

.9549

.9545

.9545

.9261

3.Imb-SMOTE vehicle0

.9591

.9600

.9622

.9631

.9659

.9671

.9718

.9736

.9797

.9819

.9848

.9894

.9894

.9320

3.Imb-SMOTE glass-0-1-2-3_vs_4-5-6

.8987

.9578

.9611

.9620

.9632

.9651

.9621

.9617

.9648

.9679

.9697

.9722

.9722

.8953

3.Imb-SMOTE haberman

.6141

.6455

.6493

.6564

.6595

.6618

.6631

.6667

.6775

.6847

.6888

.7081

.7081

.6262

3.Imb-SMOTE vehicle1

.7597

.7730

.7741

.7747

.7814

.7873

.7940

.7989

.8050

.8143

.8255

.8409

.8409

.6967

3.Imb-SMOTE vehicle2

.9625

.9734

.9761

.9780

.9795

.9809

.9840

.9863

.9903

.9922

.9927

.9931

.9931

.9600

3.Imb-SMOTE vehicle3

.7646

.7812

.7810

.7799

.7856

.7936

.7953

.8062

.8114

.8236

.8283

.8558

.8558

.7378

3.Imb-SMOTE yeast1

.7202

.7275

.7326

.7372

.7424

.7479

.7557

.7590

.7624

.7702

.7826

.7941

.7941

.7362

3.Imb-SMOTE glass0

.8214

.8402

.8421

.8526

.8568

.8563

.8599

.8658

.8709

.8805

.8931

.8987

.8987

.7716

3.Imb-SMOTE iris0

.9880

.9840

.9840

.9840

.9840

.9840

.9900

.9900

.9900

.9900

.9900

.9900

.9900

.9900

3.Imb-SMOTE pima

.7302

.7274

.7312

.7365

.7446

.7532

.7622

.7686

.7780

.7873

.8055

.8227

.8227

.7374

3.Imb-SMOTE ecoli-0_vs_1

.9796

.9826

.9826

.9826

.9826

.9826

.9824

.9824

.9824

.9824

.9835

.9835

.9835

.9728

3.Imb-SMOTE wisconsin

.9665

.9643

.9643

.9642

.9650

.9696

.9709

.9709

.9705

.9705

.9821

.9821

.9821

.9706

3.Imb-SMOTE glass1

.7498

.7281

.7276

.7375

.7420

.7504

.7582

.7659

.7745

.7796

.8039

.8475

.8475

.7717

Mean

.8379

.8711

.8722

.8741

.8766

.8795

.8836

.8868

.8910

.8960

.9025

.9101

.9101

.8281

Median

.8712

.9150

.9155

.9161

.9171

.9196

.9208

.9238

.9255

.9287

.9371

.9401

.9401

.8489

This table can be downloaded as an Excel document or as a CSV file by clicking on the following links xls and csv.

 

 

 

3.2 Results for the Number of Internal Nodes measure

 

Table 6. Number of Internal Nodes values for all algorithms over 96 datasets.

CTC

PCTBagging

C4.5

 

 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

 

1.Standard lymphography

3.72

3.28

3.12

2.56

2.16

1.92

1.40

1.36

1.00

0.72

0.04

0.00

9.40

1.Standard ecoli

12.40

12.40

11.24

9.88

8.52

7.40

5.88

5.00

3.72

2.52

1.00

0.00

18.40

1.Standard car

25.00

21.60

19.36

17.28

14.96

12.92

10.52

8.68

6.44

4.32

2.04

0.00

45.60

1.Standard nursery

12.40

11.84

10.64

9.48

8.16

7.08

5.72

4.76

3.60

2.36

1.12

0.00

31.20

1.Standard cleveland

22.48

21.52

19.32

17.16

15.00

12.84

10.52

8.68

6.44

4.36

2.12

0.00

36.00

1.Standard zoo

6.96

7.24

6.24

5.88

5.24

4.36

3.36

2.88

2.00

1.36

1.00

0.00

6.60

1.Standard glass

13.52

15.04

13.52

12.00

10.60

9.00

7.32

6.04

4.36

3.04

1.44

0.00

21.20

1.Standard flare

10.04

11.24

10.08

9.08

7.76

6.72

5.36

4.52

3.32

2.16

1.00

0.00

14.00

1.Standard abalone

51.52

53.96

48.44

43.16

37.84

32.44

26.76

21.52

16.04

10.80

5.44

0.00

91.80

1.Standard balance

28.28

35.92

32.20

28.72

25.12

21.60

17.68

14.32

10.68

7.20

3.60

0.00

36.00

1.Standard dermatology

6.56

8.52

7.52

6.84

5.96

4.96

3.88

3.56

2.56

1.68

1.00

0.00

7.80

1.Standard hepatitis

3.80

4.16

3.76

3.36

2.76

2.44

1.88

1.72

1.24

0.80

0.24

0.00

3.80

1.Standard newthyroid

6.04

7.84

6.84

6.28

5.52

4.72

3.64

3.12

2.28

1.56

0.96

0.00

5.80

1.Standard haberman

10.88

14.00

12.52

11.16

9.72

8.36

6.72

5.64

4.12

2.84

1.32

0.00

1.80

1.Standard breast

3.96

4.60

4.16

3.56

3.12

2.68

2.08

1.92

1.24

1.04

0.20

0.00

4.40

1.Standard german

25.12

28.76

25.80

23.04

20.08

17.36

14.12

11.40

8.64

5.72

2.92

0.00

26.80

1.Standard wisconsin

3.24

3.96

3.40

3.20

2.44

2.40

1.64

1.56

1.04

0.76

0.08

0.00

3.40

1.Standard contraceptive

114.20

136.64

122.84

109.28

95.64

82.00

68.08

54.64

41.00

27.36

13.80

0.00

110.00

1.Standard tictactoe

38.68

40.20

36.04

32.16

28.04

24.12

19.80

16.08

11.92

8.04

3.92

0.00

38.20

1.Standard pima

44.88

58.04

52.32

46.48

40.64

34.80

28.76

23.24

17.36

11.56

5.68

0.00

20.20

1.Standard magic

87.76

121.64

109.44

97.36

85.20

72.96

60.48

48.68

36.36

24.28

12.12

0.00

38.00

1.Standard wine

4.76

4.80

4.28

3.80

3.28

2.76

2.24

2.04

1.24

1.00

0.24

0.00

4.20

1.Standard bupa

29.40

33.40

30.04

26.84

23.32

20.04

16.48

13.36

10.04

6.56

3.32

0.00

23.60

1.Standard heart

9.52

9.80

8.72

7.84

6.84

5.76

4.64

4.04

2.88

1.96

1.00

0.00

12.20

1.Standard australian

17.24

22.72

20.40

18.12

15.92

13.64

11.08

9.08

6.80

4.60

2.32

0.00

17.40

1.Standard crx

10.24

14.04

12.64

11.32

9.96

8.60

6.72

5.44

4.08

2.72

1.40

0.00

9.80

1.Standard vehicle

67.00

97.88

88.04

78.28

68.48

58.72

48.64

39.16

29.32

19.60

9.76

0.00

61.00

1.Standard penbased

49.44

65.80

59.08

52.68

46.04

39.52

32.68

26.28

19.72

13.12

6.68

0.00

49.00

1.Standard ring

25.16

26.48

23.80

21.28

18.64

15.96

12.96

10.52

7.84

5.20

2.68

0.00

24.00

1.Standard iris

3.00

3.16

3.08

2.20

2.08

2.04

1.12

1.12

1.00

0.96

0.00

0.00

3.20

2.Imbalanced abalone19

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

2.Imbalanced yeast6

4.92

2.68

2.24

2.20

1.76

1.60

1.16

1.08

0.68

0.48

0.20

0.00

4.20

2.Imbalanced yeast5

6.00

4.96

4.36

3.92

3.36

3.04

2.12

1.92

1.40

1.04

0.40

0.00

8.20

2.Imbalanced yeast4

5.36

3.76

3.36

2.96

2.64

2.24

1.72

1.52

1.12

0.80

0.40

0.00

7.40

2.Imbalanced yeast-2_vs_8

1.00

1.00

1.00

1.00

1.00

1.00

0.00

0.00

0.00

0.00

0.00

0.00

0.80

2.Imbalanced glass5

2.56

2.40

2.40

2.04

1.40

1.36

1.04

1.04

1.00

0.36

0.00

0.00

3.00

2.Imbalanced abalone9-18

0.96

0.92

0.80

0.72

0.64

0.56

0.44

0.36

0.24

0.20

0.08

0.00

6.00

2.Imbalanced glass4

3.48

3.36

3.32

2.48

2.44

1.80

1.56

1.56

0.88

0.88

0.00

0.00

4.60

2.Imbalanced ecoli4

2.40

2.52

2.52

2.08

1.52

1.44

1.08

1.08

1.00

0.44

0.00

0.00

2.60

2.Imbalanced glass2

1.08

1.48

1.28

1.20

1.00

0.96

0.72

0.52

0.48

0.28

0.20

0.00

6.00

2.Imbalanced vowel0

9.20

9.08

8.08

7.28

6.40

5.40

4.20

3.68

2.68

1.80

1.00

0.00

6.80

2.Imbalanced page-blocks0

33.60

35.52

31.88

28.36

24.84

21.28

17.48

14.24

10.60

7.16

3.56

0.00

35.20

2.Imbalanced ecoli3

6.16

6.52

5.64

5.20

4.48

3.88

3.00

2.64

1.80

1.32

0.64

0.00

5.20

2.Imbalanced yeast3

12.84

13.48

12.08

10.84

9.28

7.96

6.44

5.52

4.08

2.64

1.28

0.00

9.80

2.Imbalanced glass6

2.40

2.76

2.76

2.24

1.76

1.52

1.24

1.24

1.00

0.52

0.00

0.00

2.40

2.Imbalanced segment0

8.36

8.72

7.72

6.88

6.08

5.12

4.00

3.60

2.64

1.84

1.00

0.00

8.60

2.Imbalanced ecoli2

5.20

5.96

5.04

4.84

4.04

3.84

2.84

2.12

1.80

1.12

0.80

0.00

6.40

2.Imbalanced new-thyroid1

2.92

3.12

3.04

2.48

2.04

1.72

1.40

1.40

1.00

0.64

0.00

0.00

4.40

2.Imbalanced new-thyroid2

3.12

3.24

3.20

2.52

2.20

1.76

1.48

1.48

1.00

0.72

0.00

0.00

3.40

2.Imbalanced ecoli1

9.72

10.40

9.40

8.40

7.20

6.28

4.96

4.12

3.20

2.00

1.00

0.00

6.00

2.Imbalanced vehicle0

18.00

17.76

15.84

14.32

12.40

10.60

8.52

7.16

5.24

3.44

1.80

0.00

19.00

2.Imbalanced glass-0-1-2-3_vs_4-5-6

4.96

5.40

4.68

4.32

3.64

3.28

2.44

2.12

1.48

1.08

0.44

0.00

4.80

2.Imbalanced haberman

8.04

12.76

11.44

10.20

8.88

7.72

6.16

5.04

3.84

2.56

1.28

0.00

1.80

2.Imbalanced vehicle1

50.60

57.12

51.40

45.76

39.96

34.32

28.40

22.80

17.12

11.36

5.68

0.00

34.60

2.Imbalanced vehicle2

14.76

14.92

13.44

11.84

10.44

8.84

7.24

6.08

4.28

3.08

1.28

0.00

14.80

2.Imbalanced vehicle3

56.96

61.36

55.00

49.12

42.80

36.84

30.40

24.52

18.28

12.24

6.08

0.00

40.80

2.Imbalanced yeast1

72.96

83.24

74.80

66.76

58.16

49.92

41.36

33.32

24.96

16.48

8.32

0.00

20.40

2.Imbalanced glass0

12.84

11.60

10.48

9.32

8.00

6.96

5.52

4.64

3.56

2.28

1.08

0.00

8.80

2.Imbalanced iris0

1.00

1.00

1.00

1.00

1.00

1.00

0.00

0.00

0.00

0.00

0.00

0.00

1.00

2.Imbalanced pima

44.92

50.68

45.68

40.48

35.48

30.32

25.08

20.36

15.16

10.20

4.96

0.00

20.20

2.Imbalanced ecoli-0_vs_1

1.04

1.00

1.00

1.00

1.00

1.00

0.00

0.00

0.00

0.00

0.00

0.00

1.00

2.Imbalanced wisconsin

2.64

2.60

2.40

2.20

1.80

1.60

1.00

1.00

0.60

0.40

0.00

0.00

3.40

2.Imbalanced glass1

13.08

12.68

11.44

10.16

8.80

7.64

6.08

5.04

3.80

2.52

1.16

0.00

9.80

3.Imb-SMOTE abalone19

42.68

25.00

22.44

20.00

17.44

15.00

12.28

10.00

7.44

5.00

2.44

0.00

63.00

3.Imb-SMOTE yeast6

17.92

13.48

12.00

10.76

9.40

8.16

6.52

5.32

3.96

2.72

1.36

0.00

20.20

3.Imb-SMOTE yeast5

6.00

5.28

4.56

4.28

3.56

3.08

2.36

2.20

1.36

1.00

0.36

0.00

10.40

3.Imb-SMOTE yeast4

26.92

22.24

19.96

17.80

15.60

13.40

10.84

8.84

6.60

4.44

2.24

0.00

40.00

3.Imb-SMOTE yeast-2_vs_8

11.08

10.36

9.36

8.24

7.28

6.16

4.96

4.20

3.08

2.12

1.00

0.00

11.80

3.Imb-SMOTE glass5

4.84

4.48

4.04

3.52

3.04

2.64

2.00

1.84

1.24

0.96

0.24

0.00

5.20

3.Imb-SMOTE abalone9-18

29.92

28.48

25.52

22.76

19.80

17.08

13.96

11.40

8.44

5.72

2.72

0.00

43.20

3.Imb-SMOTE glass4

4.04

4.12

3.80

3.16

2.80

2.40

1.84

1.72

1.12

0.96

0.12

0.00

7.20

3.Imb-SMOTE ecoli4

5.72

5.60

4.84

4.48

3.80

3.32

2.56

2.28

1.48

1.12

0.44

0.00

8.80

3.Imb-SMOTE glass2

10.28

11.32

10.20

9.08

7.96

6.84

5.48

4.48

3.32

2.24

1.08

0.00

14.60

3.Imb-SMOTE vowel0

10.64

10.80

9.72

8.60

7.52

6.48

5.12

4.32

3.24

2.20

1.04

0.00

11.20

3.Imb-SMOTE page-blocks0

61.56

64.64

58.12

51.64

45.12

38.72

32.00

25.92

19.40

13.00

6.40

0.00

115.80

3.Imb-SMOTE ecoli3

7.20

8.52

7.56

6.88

6.04

5.08

4.00

3.44

2.48

1.64

0.96

0.00

11.80

3.Imb-SMOTE yeast3

22.80

24.12

21.56

19.32

16.80

14.52

11.72

9.60

7.08

4.80

2.32

0.00

30.60

3.Imb-SMOTE glass6

5.60

6.28

5.32

5.16

4.24

3.88

2.92

2.40

1.84

1.12

0.76

0.00

7.80

3.Imb-SMOTE segment0

11.28

12.72

11.52

10.16

8.88

7.56

6.16

5.16

3.80

2.56

1.16

0.00

12.80

3.Imb-SMOTE ecoli2

9.52

12.04

10.84

9.64

8.36

7.28

5.80

4.76

3.60

2.40

1.12

0.00

15.00

3.Imb-SMOTE new-thyroid1

3.40

3.52

3.28

2.72

2.28

2.08

1.48

1.44

1.04

0.80

0.04

0.00

3.40

3.Imb-SMOTE new-thyroid2

3.60

4.28

3.92

3.28

2.92

2.60

1.92

1.68

1.24

1.00

0.24

0.00

5.20

3.Imb-SMOTE ecoli1

6.16

8.48

7.48

6.76

5.96

5.08

4.00

3.40

2.44

1.72

0.92

0.00

8.00

3.Imb-SMOTE vehicle0

18.00

21.92

19.68

17.48

15.20

13.16

10.68

8.76

6.52

4.44

2.04

0.00

28.60

3.Imb-SMOTE glass-0-1-2-3_vs_4-5-6

5.92

7.44

6.44

6.00

5.16

4.48

3.48

2.96

2.24

1.44

0.96

0.00

7.60

3.Imb-SMOTE haberman

20.72

28.52

25.60

22.76

19.92

17.16

14.00

11.36

8.44

5.76

2.76

0.00

9.80

3.Imb-SMOTE vehicle1

51.76

70.60

63.60

56.56

49.36

42.32

35.16

28.28

21.24

14.04

7.00

0.00

69.60

3.Imb-SMOTE vehicle2

14.80

15.44

13.76

12.32

10.64

9.36

7.40

6.08

4.60

3.12

1.48

0.00

17.60

3.Imb-SMOTE vehicle3

54.20

70.56

63.52

56.40

49.36

42.32

35.04

28.24

21.20

14.16

7.04

0.00

75.40

3.Imb-SMOTE yeast1

97.52

127.64

114.80

102.12

89.32

76.52

63.60

51.12

38.12

25.52

12.64

0.00

54.40

3.Imb-SMOTE glass0

12.12

14.52

13.00

11.56

10.16

8.72

6.96

5.80

4.32

2.96

1.48

0.00

12.00

3.Imb-SMOTE iris0

1.00

1.00

1.00

1.00

1.00

1.00

0.00

0.00

0.00

0.00

0.00

0.00

1.00

3.Imb-SMOTE pima

51.44

69.16

62.28

55.32

48.48

41.52

34.44

27.64

20.64

13.84

6.84

0.00

29.00

3.Imb-SMOTE ecoli-0_vs_1

1.72

2.76

2.68

2.12

2.04

1.72

1.04

1.04

0.64

0.64

0.00

0.00

3.20

3.Imb-SMOTE wisconsin

3.68

3.84

3.60

2.84

2.60

2.24

1.60

1.60

1.00

1.00

0.00

0.00

3.80

3.Imb-SMOTE glass1

16.48

20.24

18.20

16.08

14.16

12.16

9.88

8.08

6.00

4.16

1.96

0.00

13.00

Mean

18.97

21.81

19.60

17.45

15.23

13.09

10.65

8.72

6.48

4.36

2.11

0.00

19.35

Median

10.14

11.28

10.14

9.08

7.86

6.78

5.42

4.50

3.32

2.22

1.02

0.00

9.80

This table can be downloaded as an Excel document or as a CSV file by clicking on the following links xls and csv.

 

 

 

 

3.3 Results for the Time Measure

 

Table 7. Time values for all algorithms over 96 datasets.

 

CTC

PCTBagging

Bagging

C4.5

 

 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

 

 

1.Standard lymphography

79

43

51

50

50

50

51

51

51

53

55

55

450

8

1.Standard ecoli

511

298

347

341

345

344

351

348

351

351

364

381

886

19

1.Standard car

630

376

474

473

466

458

454

452

448

445

447

468

1026

18

1.Standard nursery

253

167

206

207

201

201

201

200

199

198

201

207

762

14

1.Standard cleveland

930

891

1056

1053

1042

1031

1020

1024

1030

1028

1058

1079

979

26

1.Standard zoo

109

145

184

182

180

182

183

181

185

187

187

188

997

7

1.Standard glass

334

491

586

579

585

563

558

571

576

577

602

634

767

21

1.Standard flare

747

1249

1518

1514

1498

1485

1482

1484

1463

1464

1442

1458

1262

20

1.Standard abalone

2458

3510

3843

3833

3799

3805

3810

3798

3822

3849

3924

4583

2053

139

1.Standard balance

500

1141

1373

1347

1333

1322

1324

1330

1315

1334

1308

1340

869

13

1.Standard dermatology

155

488

533

533

537

544

554

558

572

589

603

629

1295

13

1.Standard hepatitis

42

96

120

121

122

123

124

120

119

122

128

125

923

7

1.Standard newthyroid

53

129

151

148

147

149

150

151

152

160

165

188

544

7

1.Standard haberman

125

722

859

856

846

852

831

846

835

805

808

796

762

5

1.Standard breast

176

1161

1343

1313

1305

1327

1324

1363

1364

1353

1372

1351

1356

9

1.Standard german

889

4953

5772

5791

5777

5721

5708

5734

5701

5728

5760

6105

1944

51

1.Standard wisconsin

127

1053

1320

1308

1259

1251

1234

1214

1189

1194

1184

1197

867

7

1.Standard contraceptive

1255

13346

14390

14375

14363

14388

14440

14435

14480

14555

14760

15722

3530

71

1.Standard tictactoe

270

1808

2328

2292

2287

2253

2229

2212

2194

2172

2179

2247

1406

15

1.Standard pima

458

3651

4040

4030

4028

4018

4027

4026

4040

4054

4118

4543

1926

33

1.Standard magic

6765

56783

58431

58402

58421

58352

58408

58541

58565

58798

59453

73885

17742

886

1.Standard wine

54

507

566

578

583

596

605

604

647

656

739

766

741

11

1.Standard bupa

122

1369

1557

1560

1560

1565

1564

1570

1573

1578

1596

1673

977

13

1.Standard heart

55

793

937

938

939

940

942

947

951

969

990

1038

1171

13

1.Standard australian

297

4758

5457

5462

5464

5478

5488

5493

5506

5577

5628

5933

1689

33

1.Standard crx

172

2869

3349

3348

3360

3353

3347

3358

3368

3370

3440

3645

1647

27

1.Standard vehicle

686

20639

21096

21058

21099

21168

21257

21372

21618

22054

22703

24541

4825

68

1.Standard penbased

1171

35677

36118

36162

36279

36484

36856

37402

38108

39030

40313

44975

9909

106

1.Standard ring

8851

143319

144546

144460

144514

144546

145078

147028

150331

154563

160437

169448

27001

586

1.Standard iris

16

81

98

99

99

100

102

102

99

101

106

107

850

6

2.Imbalanced abalone19

2488

206

273

274

275

271

275

273

273

271

271

275

397

287

2.Imbalanced yeast6

417

118

149

150

149

150

150

149

151

152

155

156

379

11

2.Imbalanced yeast5

217

74

87

87

85

87

88

88

89

92

99

104

373

12

2.Imbalanced yeast4

887

335

409

408

409

405

404

406

403

404

406

413

398

14

2.Imbalanced yeast-2_vs_8

172

94

117

117

118

119

125

125

124

124

125

122

402

7

2.Imbalanced glass5

64

39

56

54

53

55

52

54

50

54

56

55

453

8

2.Imbalanced abalone9-18

661

456

575

577

574

575

575

574

574

575

577

579

445

40

2.Imbalanced glass4

79

66

82

83

82

82

83

82

84

85

95

96

325

11

2.Imbalanced ecoli4

73

67

88

85

87

88

88

88

88

94

100

99

368

8

2.Imbalanced glass2

119

129

165

167

166

168

170

168

170

171

170

173

411

13

2.Imbalanced vowel0

640

732

774

776

779

786

798

805

833

864

922

1117

767

139

2.Imbalanced page-blocks0

9547

12316

13391

13398

13403

13404

13416

13432

13485

13625

14224

16419

4433

596

2.Imbalanced ecoli3

119

169

210

211

211

209

208

203

209

205

212

220

316

8

2.Imbalanced yeast3

384

543

622

621

620

621

622

624

625

633

652

688

551

16

2.Imbalanced glass6

65

115

149

150

150

148

149

147

150

154

165

165

368

9

2.Imbalanced segment0

3259

6279

6879

6881

6887

6893

7028

7088

7284

7550

7937

9307

3490

551

2.Imbalanced ecoli2

106

226

274

276

272

270

272

273

275

278

281

296

391

7

2.Imbalanced new-thyroid1

34

72

95

92

91

92

92

94

93

95

106

105

340

7

2.Imbalanced new-thyroid2

21

46

53

55

56

52

57

57

57

59

70

70

389

6

2.Imbalanced ecoli1

93

298

366

363

359

361

357

359

356

360

365

389

428

10

2.Imbalanced vehicle0

590

2313

2445

2451

2459

2471

2495

2516

2552

2607

2695

2912

990

31

2.Imbalanced glass-0-1-2-3_vs_4-5-6

71

246

298

296

297

298

302

303

313

316

335

354

446

10

2.Imbalanced haberman

109

609

728

724

720

715

710

706

698

686

676

672

386

8

2.Imbalanced vehicle1

1297

6500

6909

6909

6914

6928

6954

6984

7036

7116

7264

7786

1707

49

2.Imbalanced vehicle2

508

2515

2678

2679

2688

2697

2716

2743

2842

2920

3063

3245

1186

29

2.Imbalanced vehicle3

1180

5727

5922

5925

5943

5958

5989

6025

6077

6155

6300

6909

2035

56

2.Imbalanced yeast1

633

3578

3902

3903

3901

3910

3919

3923

3923

3916

3906

4187

1136

30

2.Imbalanced glass0

104

709

780

782

784

783

793

801

807

831

860

915

589

14

2.Imbalanced iris0

15

35

47

50

47

48

63

62

60

59

62

58

324

3

2.Imbalanced pima

452

3753

4151

4150

4147

4142

4148

4148

4153

4148

4207

4685

1295

35

2.Imbalanced ecoli-0_vs_1

22

117

152

151

151

151

186

187

186

187

188

188

396

5

2.Imbalanced wisconsin

36

236

310

309

306

305

313

312

313

316

321

322

503

8

2.Imbalanced glass1

124

955

1062

1063

1067

1068

1074

1076

1086

1111

1167

1235

752

13

3.Imb-SMOTE abalone19

4744

448

446

443

440

438

436

437

437

438

443

481

439

7766

3.Imb-SMOTE yeast6

733

254

254

252

250

249

247

246

247

249

254

269

342

403

3.Imb-SMOTE yeast5

546

224

223

222

218

218

218

218

222

223

236

242

250

467

3.Imb-SMOTE yeast4

824

366

366

364

362

360

359

359

361

365

371

408

394

334

3.Imb-SMOTE yeast-2_vs_8

379

235

234

230

227

224

222

221

220

221

223

233

316

50

3.Imb-SMOTE glass5

138

110

112

110

109

108

107

106

106

106

106

107

361

34

3.Imb-SMOTE abalone9-18

813

685

678

668

660

653

647

643

638

637

638

685

438

220

3.Imb-SMOTE glass4

120

123

123

123

122

122

121

121

122

122

125

126

338

32

3.Imb-SMOTE ecoli4

137

146

145

145

142

142

141

141

142

142

146

149

453

33

3.Imb-SMOTE glass2

231

329

328

323

320

318

315

314

314

315

320

331

437

50

3.Imb-SMOTE vowel0

840

1062

1061

1057

1056

1055

1062

1077

1106

1141

1191

1371

739

622

3.Imb-SMOTE page-blocks0

12003

16107

16094

16075

16065

16059

16061

16071

16103

16184

16793

20428

5863

2798

3.Imb-SMOTE ecoli3

166

289

286

283

285

277

280

277

279

280

286

301

334

32

3.Imb-SMOTE yeast3

1117

1817

1808

1803

1795

1788

1784

1782

1779

1785

1841

2022

776

320

3.Imb-SMOTE glass6

86

174

178

178

175

173

175

174

178

179

182

199

372

28

3.Imb-SMOTE segment0

6412

13012

13014

13016

13017

13024

13069

13218

13606

14207

15432

17972

6231

3269

3.Imb-SMOTE ecoli2

160

412

410

405

401

399

397

396

398

402

410

438

396

33

3.Imb-SMOTE new-thyroid1

45

118

119

118

120

118

121

119

123

124

132

131

291

15

3.Imb-SMOTE new-thyroid2

46

111

109

112

109

109

110

109

112

114

121

123

289

15

3.Imb-SMOTE ecoli1

131

493

491

489

491

491

486

490

491

496

510

550

506

25

3.Imb-SMOTE vehicle0

618

2498

2497

2489

2488

2487

2495

2506

2539

2587

2693

2910

1039

54

3.Imb-SMOTE glass-0-1-2-3_vs_4-5-6

84

336

333

334

333

330

337

338

343

351

359

390

380

23

3.Imb-SMOTE haberman

139

813

801

795

788

783

779

772

764

751

730

721

389

17

3.Imb-SMOTE vehicle1

1293

6727

6722

6717

6726

6739

6760

6797

6850

6953

7127

7717

1747

93

3.Imb-SMOTE vehicle2

500

2699

2699

2703

2707

2721

2741

2790

2876

2959

3074

3293

1171

52

3.Imb-SMOTE vehicle3

1492

7573

7566

7563

7569

7584

7605

7638

7698

7803

8009

8735

1954

102

3.Imb-SMOTE yeast1

1267

7331

7306

7286

7276

7272

7278

7284

7292

7302

7329

8465

2172

158

3.Imb-SMOTE glass0

119

769

767

770

771

777

781

789

808

824

870

949

589

28

3.Imb-SMOTE iris0

15

45

48

47

48

49

56

57

56

57

56

56

264

11

3.Imb-SMOTE pima

442

3719

3714

3712

3713

3721

3733

3748

3763

3794

3850

4441

1509

63

3.Imb-SMOTE ecoli-0_vs_1

23

137

140

139

139

140

151

151

155

154

176

174

301

12

3.Imb-SMOTE wisconsin

79

807

803

780

769

762

742

741

728

728

715

715

420

15

3.Imb-SMOTE glass1

122

956

954

961

958

968

973

980

997

1011

1061

1193

639

24

Mean

924

4407

4559

4556

4556

4558

4575

4609

4668

4751

4895

5416

1567

224

Median

224

500

581

579

584

585

590

589

601

611

621

653

689

24

 

This table can be downloaded as an Excel document or as a CSV file by clicking on the following links xls and csv.

 

 

 



[1] The iris data set is an exception. It is already balanced. Subsamples are smaller than usual.