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Table 3 Comparison of random forest with other classifiers

From: ReRF-Pred: predicting amyloidogenic regions of proteins based on their pseudo amino acid composition and tripeptide composition

  ACC SE SP MCC
Random forest 0.823 0.640 0.926 0.606
AdaBoost 0.751 0.605 0.834 0.450
Bagging 0.796 0.650 0.879 0.549
Naïve Bayes 0.773 0.693 0.818 0.510
LibSVM 0.796 0.585 0.916 0.545
Decision tree 0.779 0.658 0.848 0.515
LWL 0.732 0.581 0.817 0.408
JRip 0.773 0.583 0.880 0.492
KNN (K = 3) 0.791 0.566 0.918 0.532
MLP 0.454 0.734 0.296 0.031