Table 8 Comparison of G-mean values for testing performance of KNN models trained on training sets processed by various sampling algorithms.

0.7299 ± 0.0005

0.7310 ± 0.0005

0.7265 ± 0.0004

0.7256 ± 0.0004

0.7298 ± 0.0007

0.7274 ± 0.0005

0.7372 ± 0.0009

0.7381 ± 0.0005

0.7071 ± 0.0319

0.7002 ± 0.0649

0.6753 ± 0.0523

0.6790 ± 0.0487

0.6897 ± 0.0482

0.7162 ± 0.0590

0.6930 ± 0.0587

0.7084 ± 0.0578

0.8871 ± 0.0008

0.9038 ± 0.0004

0.9077 ± 0.0005

0.9055 ± 0.0004

0.8953 ± 0.0007

0.9033 ± 0.0004

0.8884 ± 0.0009

0.8980 ± 0.0005

0.8624 ± 0.0412

0.8848 ± 0.0300

0.8746 ± 0.0318

0.8764 ± 0.0474

0.8763 ± 0.0338

0.8338 ± 0.0256

0.8863 ± 0.0552

0.9024 ± 0.0315

0.7533 ± 0.0061

0.7930 ± 0.0324

0.7863 ± 0.0324

0.8599 ± 0.0264

0.7654 ± 0.0323

0.7696 ± 0.0296

0.6851 ± 0.0250

0.8646 ± 0.0322

0.6589 ± 0.0033

0.6866 ± 0.0029

0.6984 ± 0.0025

0.6652 ± 0.0031

0.6588 ± 0.0018

0.6604 ± 0.0027

0.5454 ± 0.0102

0.6988 ± 0.0038

0.6794 ± 0.0111

0.7653 ± 0.0029

0.7577 ± 0.0056

0.7411 ± 0.0058

0.7729 ± 0.0013

0.7620 ± 0.0031

0.5287 ± 0.0148

0.7867 ± 0.0025

0.3055 ± 0.0146

0.5058 ± 0.0108

0.4979 ± 0.0118

0.5019 ± 0.0108

0.4812 ± 0.0180

0.4749 ± 0.0117

0.1016 ± 0.0082

0.5106 ± 0.0120

0.2423 ± 0.0278

0.4124 ± 0.0341

0.3892 ± 0.0266

0.2961 ± 0.0309

0.3705 ± 0.0246

0.4005 ± 0.0291

0.0663 ± 0.0058

0.4349 ± 0.0246

0.6784 ± 0.0105

0.7037 ± 0.0091

0.6909 ± 0.0108

0.7042 ± 0.0111

0.7132 ± 0.0079

0.7123 ± 0.0116

0.5864 ± 0.0163

0.7394 ± 0.0146

0.3302 ± 0.0198

0.4355 ± 0.0186

0.4206 ± 0.0270

0.3791 ± 0.0246

0.4894 ± 0.0255

0.4895 ± 0.0353

0.3309 ± 0.0196

0.4839 ± 0.0241

0.5830 ± 0.0331

0.6629 ± 0.0045

0.6557 ± 0.0214

0.6311 ± 0.0135

0.6460 ± 0.0146

0.6469 ± 0.0129

0.3764 ± 0.0315

0.6284 ± 0.0179

0.2324 ± 0.0175

0.3133 ± 0.0443

0.2844 ± 0.0199

0.3400 ± 0.0411

0.2929 ± 0.0268

0.2877 ± 0.0377

0.0736 ± 0.0088

0.3176 ± 0.0260