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Table 5 Prediction results of machine-learning methods on independent test set

From: Rigorous assessment and integration of the sequence and structure based features to predict hot spots

Method P R F1
BaysNet 0.65 0.54 0.59
Logistic 0.62 0.63 0.62
RBFNNetwork 0.63 0.69 0.66
Decision Tree 0.66 0.60 0.63
Random Forest 0.68 0.55 0.61
Rules NNge 0.67 0.56 0.61
Lazy Kstar 0.63 0.51 0.57
Random Tree 0.61 0.50 0.55
Sequence-based SVM 0.69 0.68 0.68