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Table 4 BREAST dataset: Accuracy using 3 seeds and 4-fold cross validation: comparison with PLS-DA, Random Forest, Logistic Regression, SVM and NN

From: Learning a confidence score and the latent space of a new supervised autoencoder for diagnosis and prognosis in clinical metabolomic studies

Breast

SAE \(\ell _1\)

SAE \(\ell _2\)

PLS-DA

RF

SVM

NN

Accuracy \(\%\)

90.15

89.05

86.58

80.23

83.20

89.04

AUC \(\%\)

84.88

81.62

83.07

88.02

77.64

80.34

F1 Score

85.17

83.66

76.01

71.07

76.06

82.94

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BMC Bioinformatics

ISSN: 1471-2105

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