BMC Bioinformatics

Table 3 Five-fold cross-validations of meta classifiers

From: A meta-learning approach for B-cell conformational epitope prediction

Classifier	TPR	FPR	Precision	Accuracy	F-score	MCC	AUC
2-level (ANN)^a	0.514	0.019	0.705	0.944	0.594	0.573	0.748
2-level (C4.5)^a	0.511	0.023	0.663	0.941	0.577	0.551	0.744
2-level (k-NN)^a	0.496	0.012	0.783	0.949	0.607	0.599	0.742
2-level (SVM)^a	0.593	0.009	0.848	0.959	0.697	0.689^d	0.920
3-level Stacking^b	0.579	0.009	0.850	0.958	0.689	0.682^d	0.925
Cascade^c	0.588	0.010	0.843	0.959	0.693	0.684^d	0.925

^aTwo-level stacking meta classifiers with ANN, C4.5, k-NN, or SVM as the top-level meta learner.
^bThree-level stacking meta classifier (Figure 3).
^cCascade meta classifier (Figure 4).
^dPaired t test showed no significant difference.

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ISSN: 1471-2105

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