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Table 8 F1-score values of the proposed RBNRO-DE against popular ML classifiers

From: Gene selection via improved nuclear reaction optimization algorithm for cancer classification in high-dimensional data

Benchmark

RBNRO-DE with k-NN

RBNRO-DE with SVM

k-NN

SVM

DT

RF

XGBoost

BLCA

1.0000

1.0000

0.9814

0.9937

0.9937

0.9693

0.9875

CESC

0.9919

1.0000

0.9919

0.9836

0.9919

0.9919

0.9919

CHOL

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

0.9091

COAD

1.0000

1.0000

0.9913

0.9913

0.9913

0.9913

0.9828

ESCA

0.9867

0.9956

0.9867

0.9867

0.9737

0.9867

0.9867

GBM

1.0000

1.0000

0.9836

1.0000

1.0000

1.0000

1.0000

HNSC

0.9964

1.0000

0.9749

0.9282

0.9694

0.9652

0.9697

KICH

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

KIRC

0.9990

1.0000

0.9903

0.9855

0.9364

0.9585

0.9856

KIRP

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

LIHC

1.0000

1.0000

1.0000

1.0000

0.9865

0.9799

0.9865

LUAD

0.9950

0.9955

0.9900

0.9900

0.9800

0.9950

0.9900

LUSC

1.0000

1.0000

0.9843

0.9895

0.9368

0.9845

0.9896

PAAD

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

PCPG

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

READ

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

SARC

0.9905

0.9981

0.9905

0.9905

0.9905

0.9905

0.9905

SKCM

1.0000

1.0000

1.0000

1.0000

0.9756

1.0000

1.0000

STAD

1.0000

0.9943

0.9634

0.9634

0.9193

0.9506

0.9634

THCA

1.0000

1.0000

1.0000

1.0000

0.9800

1.0000

1.0000

THYM

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

1.0000

UCEC

0.9995

1.0000

0.9577

0.9577

0.9577

0.9722

0.9722

Ranking (\(\text {W|T|L}\))

1|14|7

\(\mathbf {7|14|1}\)

0|10|12

0|11|11

0|8|14

0|10|12

0|9|13