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Table 2 Comparison of the performance of RF, SVM and ANN under all encoding procedures with both balanced and imbalanced training dataset

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

EP

MLA

Balanced Dataset

Imbalanced Dataset

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

RF

0.954

0.924

0.940

0.932

0.939

0.939

0.878

0.842

0.896

0.865

0.880

0.869

0.869

0.739

(0.014)

(0.014)

(0.010)

(0.012)

(0.010)

(0.010)

(0.020)

(0.064)

(0.018)

(0.032)

(0.049)

(0.030)

(0.028)

(0.043)

SVM

0.935

0.930

0.933

0.931

0.933

0.933

0.865

0.104

0.982

0.185

0.349

0.320

0.543

0.180

(0.015)

(0.017)

(0.015)

(0.015)

(0.016)

(0.016)

(0.031)

(0.027)

(0.018)

(0.041)

(0.031)

(0.040)

(0.013)

(0.061)

ANN

0.892

0.896

0.894

0.895

0.894

0.894

0.787

0.032

0.988

0.061

0.136

0.178

0.510

0.068

(0.064)

(0.080)

(0.063)

(0.062)

(0.066)

(0.065)

(0.129)

(0.026)

(0.010)

(0.046)

(0.032)

(0.065)

(0.011)

(0.055)

P-2

RF

0.937

0.901

0.920

0.911

0.919

0.919

0.838

0.883

0.894

0.888

0.891

0.888

0.889

0.777

(0.020)

(0.016)

(0.016)

(0.018)

(0.016)

(0.016)

(0.033)

(0.038)

()

(0.025)

(0.030)

(0.019)

(0.019)

(0.035)

SVM

0.720

0.773

0.740

0.752

0.746

0.746

0.493

0.321

0.989

0.482

0.689

0.563

0.655

0.417

(0.029)

(0.106)

(0.041)

(0.026)

(0.049)

(0.051)

(0.108)

(0.051)

(0.008)

(0.055)

(0.053)

(0.043)

(0.025)

(0.048)

ANN

0.775

0.777

0.776

0.776

0.776

0.776

0.552

0.305

0.978

0.460

0.661

0.546

0.642

0.383

(0.067)

(0.037)

(0.049)

(0.059)

(0.048)

(0.045)

(0.090)

(0.049)

(0.014)

(0.052)

(0.051)

(0.043)

(0.022)

(0.046)

P-3

RF

0.940

0.908

0.925

0.917

0.924

0.924

0.848

0.879

0.891

0.884

0.888

0.885

0.885

0.770

(0.017)

(0.015)

(0.012)

(0.014)

(0.012)

(0.012)

(0.246)

(0.044)

(0.022)

(0.029)

(0.034)

(0.022)

(0.022)

(0.042)

SVM

0.789

0.807

0.796

0.800

0.798

0.798

0.595

0.249

0.988

0.395

0.609

0.496

0.619

0.352

(0.044)

(0.068)

(0.042)

(0.042)

(0.046)

(0.045)

(0.090)

(0.052)

(0.008)

(0.062)

(0.056)

(0.049)

(0.026)

(0.055)

ANN

0.757

0.760

0.758

0.759

0.759

0.759

0.517

0.272

0.979

0.421

0.626

0.516

0.626

0.355

(0.118)

(0.099)

(0.067)

(0.098)

(0.057)

(0.048)

(0.086)

(0.066)

(0.009)

(0.081)

(0.072)

(0.064)

(0.034)

(0.076)

  1. The values inside the brackets () are the standard errors
  2. EP encoding procedure, MLA machine learning approaches