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Table 4 The total number of missing rate on the numerical datasets

From: Adaptive multiple imputations of missing values using the class center

Datasets

Missing rate

10%

20%

30%

40%

50%

c\(^*\)

i\(^*\)

c

i

c

i

c

i

c

i

Blood

6,059

673

5,386

1,346

4,712

2,020

4,039

2,693

3,366

3,366

Ecoli

2,117

235

1,882

470

1,646

706

1,411

941

1,176

1,176

Glass

1,733

193

1,541

385

1,348

578

1,156

770

963

963

Ionosphere

10,741

1,193

9,547

2,387

8,354

3,580

7,160

4,774

5,967

5,967

Iris

540

60

480

120

420

180

360

240

300

300

Liver cancer

5,247

583

4,664

1,166

4,081

1,749

3,498

2,332

2,915

2,915

Optdigits

323,712

35,968

287,744

71,936

251,776

107,904

215,808

143,872

179,840

179,840

Pima

5,530

614

4,915

1,229

4,301

1,843

3,686

2,458

3,072

3,072

Sonar

11,232

1,248

9,984

2,496

8,736

3,744

7,488

4,992

6,240

6,240

Wine

2,083

231

1,851

463

1,620

694

1,388

926

1,157

1,157

Yeast

10,685

1,187

9,498

2,374

8,310

3,562

7,123

4,749

5,936

5,936

Column 2C

1,674

186

1,488

372

1,302

558

1,116

744

930

930

Column 3C

1,674

186

1,488

372

1,302

558

1,116

744

930

930

  1. \(^*\)c = complete data, i = incomplete data