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Table 4 Prognostic performance of classifiers modelled by SVM, LDA, BDA and RF for AMIP

From: Comparison of different statistical approaches for urinary peptide biomarker detection in the context of coronary artery disease

  1. The values shown are the areas under the curve of Receiver Operating Characteristic (ROC) curve analyses
  2. AMIP acute myocardial infarction prognostication, SVM support vector machine, DDA diagonal discriminant analysis, LDA linear discriminant analysis, BDA binary discriminant analysis, RF random forests, BM biomarker; ≥ 3, biomarkers present in at least 3 out of the 5 biomarker patterns resulting from the different discovery approaches; ≥ 2, biomarkers present in at least 2 out of the 5 biomarker patterns resulting from the different discovery approaches
  3. * P < 0.05 for AMIP BDA vs. AMIP cat-score, AMIP ≥ 3 and AMIP ≥ 2
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BMC Bioinformatics

ISSN: 1471-2105

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