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Table 4 Performance of one-vs-rest binary classifiers

From: CONFIGURE: A pipeline for identifying context specific regulatory modules from gene expression data and its application to breast cancer

  Luminal A Luminal B HER2 Basal-like Average
  Accuracy
SVM-RMES 0.9366 0.8722 0.9627 0.9907 0.9405
SVM-Gene expression 0.9104 0.8741 0.9664 0.9841 0.9338
SVM-Gene expression (Hallmarks) 0.9291 0.8657 0.958 0.9888 0.9354
COSSY 0.8871 0.7836 0.9067 0.9813 0.8897
Dominant Class Prediction 0.6353 0.6549 0.8983 0.8116 0.75
  F1-Score
SVM-RMES 0.913 0.8105 0.7959 0.9747 0.8736
SVM-Gene expression 0.8772 0.8143 0.8378 0.958 0.8719
SVM-Gene expression (Hallmarks) 0.9033 0.8 0.7887 0.9698 0.8655
COSSY 0.8428 0.8542 0.3101 0.9506 0.7394
Dominant Class Prediction 0 0 0 0 0