Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach

Table 6

Performance evaluation of the classifiers for the non-DDI and DDI groups.

Group	Method	Sensitivity	Specificity	Accuracy	AUC
Non-DDI	C4.5	0.705/0.091	0.806/0.078	0.759/0.061	0.784/0.065
	CART	0.696/0.095	0.825/0.067	0.765/0.055	0.791/0.057
	RF	0.782/0.090	0.888/0.054	0 0.839/0.041	0.912/0.032
	kNN	0.619/0.172	0.547/0.162	0.592/0.068	0.606/0.070
	LGR	0.566/0.145	0.715/0.117	0.648/0.078	0.661/0.097
	MLP	0.741/0.091	0.871/0.057	0.809/0.059	0.813/0.071
DDI	C4.5	0.701/0.060	0.759/0.050	0.732/0.029	0.774/0.030
	CART	0.728/0.051	0.776/0.050	0.754/0.031	0.795/0.031
	RF	0.790/0.050	0.817/0.043	0.805/0.027	0.892/0.020
	kNN	0.545/0.094	0.651/0.087	0.602/0.042	0.634/0.048
	LGR	0.464/0.139	0.621/0.145	0.551/0.042	0.556/0.058
	MLP	0.745/0.058	0.799/0.042	0.774/0.037	0.777/0.051