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Table 4 Overall performance of all methods on multi-classification for all subtypes of breast cancer

From: Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning

Methods

Accuracy

Precision-macro

Recall-macro

F1-macro

Ensmble EN

0.800

0.859

0.759

0.806

Ensmble RF

0.743

0.748

0.630

0.684

Concate EN

0.800

0.859

0.759

0.806

Concate RF

0.790

0.838

0.720

0.775

DIABLO

0.604

0.589

0.632

0.609

SMPSL

0.810

0.793

0.720

0.755

DeepMo

0.849

0.884

0.820

0.851

DSCCN

0.906

0.941

0.905

0.922

  1. The best results are marked in bold
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BMC Bioinformatics

ISSN: 1471-2105

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