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Table 4 The results of mean effectiveness on mRNA Sequencing (top 10)

From: A feature selection method based on multiple kernel learning with expression profiles of different types

Methods

SVM-RFE

SVM-RCE

mRMR

IMRelief

SlimPLS

OSFS

FGM

SMKL-FS

KIDNEY

0.912

0.952

0.965

0.949

0.898

0.914

0.951

0.957

BRCA

0.938

0.982

0.973

0.953

0.871

0.934

0.928

0.984

LUNG

0.957

0.977

0.993

0.932

0.942

0.867

0.931

0.997

HNSC

0.930

0.949

0.983

0.908

0.844

0.900

0.977

0.948

LIHC

0.893

0.937

0.962

0.919

0.900

0.798

0.952

0.958

PRAD

0.932

0.928

0.971

0.893

0.779

0.764

0.966

0.953

STAD

0.907

0.895

0.970

0.945

0.758

0.848

0.898

0.963

THCA

0.945

0.954

0.975

0.933

0.883

0.844

0.903

0.970

Mean

0.927

0.947

0.974

0.929

0.859

0.859

0.938

0.966