Skip to main content

Table 5 Standard errors of different performance metrics for Bagging, Boosting, Logistic regression, kNN and Naïve Bayes classifiers for all the three encoding procedures under both balanced and imbalanced situations

From: Prediction of donor splice sites using random forest with a new sequence encoding approach

EP

MD

Balanced

Imbalanced

TPR

TNR

F (α = 1)

F (β = 2)

G-mean

WA

MCC

TPR

TNR

F (α = 1)

F (β = 2)

G-mean

WA

MCC

P-1

BG

0.0201

0.0178

0.0114

0.0156

0.0113

0.0113

0.0226

0.0234

0.0036

0.0409

0.0282

0.0474

0.0108

0.0334

BS

0.0146

0.0149

0.0111

0.0125

0.0113

0.0112

0.0224

0.0177

0.3156

0.0334

0.0218

0.0715

0.1652

0.0504

LG

0.0569

0.0740

0.0601

0.0575

0.0624

0.0621

0.1238

0.0065

0.0056

0.0121

0.0076

0.0313

0.0045

0.0267

NB

0.0630

0.0826

0.0560

0.0571

0.0573

0.0577

0.1169

0.0357

0.1043

0.0500

0.0390

0.0439

0.0549

0.1579

KN

0.1502

0.1279

0.1386

0.1454

0.1364

0.1354

0.2701

0.0221

0.3023

0.0389

0.0267

0.0765

0.1595

0.0799

P-2

BG

0.0201

0.0272

0.0192

0.0188

0.0201

0.0200

0.0397

0.0261

0.0060

0.0429

0.0310

0.0421

0.0130

0.0364

BS

0.0207

0.0179

0.0161

0.0184

0.0163

0.0163

0.0327

0.0273

0.0033

0.0456

0.0325

0.0461

0.0134

0.0358

LG

0.0688

0.0799

0.0617

0.0644

0.0630

0.0632

0.1272

0.0182

0.0148

0.0290

0.0214

0.0273

0.0107

0.0410

NB

0.0546

0.0629

0.0421

0.0472

0.0405

0.0407

0.0824

0.0316

0.0733

0.0487

0.0363

0.0436

0.0426

0.1342

KN

0.0925

0.0811

0.0362

0.0681

0.0266

0.0280

0.0598

0.0235

0.0044

0.0337

0.0269

0.0282

0.0117

0.0270

P-3

BG

0.0156

0.0186

0.0117

0.0130

0.0120

0.0119

0.0237

0.0185

0.0052

0.0291

0.0217

0.0267

0.0089

0.0235

BS

0.0121

0.0178

0.0102

0.0102

0.0108

0.0107

0.0210

0.0194

0.0039

0.0324

0.0231

0.0323

0.0095

0.0256

LG

0.0406

0.0586

0.0376

0.0377

0.0409

0.0402

0.0795

0.0210

0.0116

0.0334

0.0247

0.0303

0.0132

0.0440

NB

0.0380

0.0689

0.0330

0.0323

0.0372

0.0368

0.0735

0.0254

0.0434

0.0397

0.0295

0.0333

0.0286

0.0913

KN

0.1017

0.0829

0.0629

0.0842

0.0566

0.0544

0.1076

0.0292

0.0078

0.0504

0.0352

0.0629

0.0116

0.0334

  1. MD methods, EP encoding procedures, BG bagging, BS boosting, LG logistic regression, NB naïve bayes, KN K nearest neighbor