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Table 4 Comparison of results for binary relevance (baseline) and classifiers chain, by ten-fold cross-validation

From: Selectivity profiling of BCRP versus P-gp inhibition: from automated collection of polypharmacology data to multi-label learning

Algorithms

Macro-accuracy

Macro-MCC

Macro-AUC

Binary relevance, Logistic Regression

0.812

0.594

0.793

Classifiers chain, Logisitic Regression

0.812

0.594

0.793

Binary relevance, RandomForest

0.835

0.641

0.808

Classifiers chain, RandomForest

0.836

0.643

0.809

Binary relevance, SVM

0.766

0.504

0.749

Classifiers chain, SVM

0.767

0.504

0.750

  1. In italic letters, the model that gives the best results