Skip to main content

Table 4 Performances of individual feature-based models constructed by RF on the benchmark datasets

From: Sequence-based bacterial small RNAs prediction using ensemble learning strategies

Index

AUC

ACC

Balanced

Imbalanced

Balanced

Imbalanced

1:1

1:2

1:3

1:4

1:5

1:1

1:2

1:3

1:4

1:5

F1

0.682

0.718

0.730

0.729

0.738

0.560

0.691

0.754

0.804

0.840

F2

0.829

0.847

0.862

0.865

0.868

0.756

0.789

0.836

0.863

0.877

F3

0.909

0.917

0.921

0.928

0.930

0.834

0.856

0.887

0.905

0.915

F4

0.923

0.933

0.930

0.934

0.933

0.860

0.884

0.906

0.921

0.930

F5

0.912

0.894

0.872

0.869

0.863

0.842

0.864

0.882

0.896

0.910

F6

0.769

0.808

0.822

0.832

0.840

0.679

0.766

0.809

0.843

0.866

F7

0.880

0.902

0.910

0.917

0.922

0.797

0.842

0.870

0.894

0.909

F8

0.913

0.924

0.929

0.938

0.939

0.835

0.871

0.901

0.916

0.927

F9

0.632

0.657

0.667

0.679

0.691

0.516

0.619

0.707

0.755

0.791

F10

0.842

0.847

0.865

0.875

0.875

0.765

0.796

0.836

0.867

0.882

F11

0.924

0.926

0.933

0.941

0.944

0.855

0.879

0.901

0.920

0.930

F12

0.938

0.949

0.948

0.954

0.954

0.880

0.902

0.918

0.931

0.942

F13

0.937

0.932

0.923

0.924

0.920

0.874

0.897

0.910

0.925

0.936

F14

0.895

0.883

0.886

0.888

0.884

0.827

0.805

0.835

0.864

0.876

F15

0.931

0.922

0.922

0.924

0.921

0.862

0.855

0.876

0.895

0.902

F16

0.902

0.894

0.890

0.890

0.887

0.825

0.833

0.859

0.882

0.897

F17

0.905

0.898

0.901

0.903

0.899

0.825

0.822

0.854

0.877

0.897