Table 4. Prediction performance on 2136 Gal4 variants.

Feature vector input attributes based on in silico mutagenesis using tessellation of the Gal4 dimer.

Method	Se	Sp	PPV	BAR	MCC	AUC
10-fold CV classification:
RF	0.91	0.90	0.93	0.91	0.81	0.97
SVM	0.91	0.82	0.88	0.87	0.74	0.94
DT	0.89	0.87	0.91	0.88	0.76	0.93
NN	0.91	0.83	0.89	0.87	0.75	0.88
10-fold CV regression:
REPTree (r = 0.80)	0.96	0.86	0.91	0.91	0.83	–
SVR (r = 0.72)	0.92	0.84	0.89	0.88	0.77	–