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Table 4 Comparison of cancer type prediction accuracy for SVM classifiers trained based on different dataset

From: methCancer-gen: a DNA methylome dataset generator for user-specified cancer type based on conditional variational autoencoder

Cancer

Number of testing samples

TCGA only

TCGA & benchmark

TCGA & methCancer-gen

   

Number of generated dataset for each cancer type

   

100

200

300

100

200

300

BRCA

313

0.796

0.796

0.796

0.796

0.799

0.802

0.809

COAD

102

0.922

0.922

0.922

0.922

0.931

0.951

0.951

GBM

71

0.972

0.972

0.972

0.972

0.972

0.972

0.972

KIRC

45

0.733

0.733

0.733

0.733

0.733

0.733

0.733

LUAD

162

0.969

1.000

1.000

1.000

1.000

1.000

1.000

PAAD

166

0.139

0.168

0.168

0.175

0.398

0.434

0.434

PRAD

20

0.700

0.700

0.700

0.700

0.700

0.700

1.000

SKCM

159

0.868

0.887

0.887

0.887

0.887

0.887

0.931

Average

0.751

0.761

0.761

0.762

0.799

0.809

0.823