SNF-NN: computational method to predict drug-disease interactions using similarity network fusion and neural networks

Table 2 SNF-NN performance comparison with baseline machine learning methods on the SND benchmark dataset

Method	Accuracy	Specificity	Precision	Recall	F1-score	MCC	AUC-ROC	AUC-PR
SAMME	0.682	0.841	0.767	0.523	0.621	0.384	0.682	0.764
DT	0.553	0.985	0.888	0.122	0.214	0.211	0.553	0.725
GPC	0.646	0.676	0.655	0.615	0.634	0.292	0.646	0.731
KNN	0.650	0.619	0.641	0.681	0.661	0.300	0.650	0.741
GNB	0.669	0.586	0.645	0.751	0.694	0.342	0.669	0.760
QDA	0.649	0.632	0.646	0.666	0.654	0.300	0.649	0.740
RF	0.533	0.692	0.635	0.374	0.354	0.112	0.533	0.661
Linear-SVM	0.702	0.718	0.709	0.685	0.697	0.404	0.702	0.776
RBF-SVM	0.535	0.949	0.704	0.120	0.204	0.124	0.535	0.632
SNF-NN	0.796	0.777	0.785	0.816	0.800	0.593	0.867	0.876

ISSN: 1471-2105