BMC Medical Informatics and Decision Making

Table 7 Number of feature and overall accuracy of models

From: Identification of clinical factors related to prediction of alcohol use disorder from electronic health records using feature selection methods

Gender	Number of features	Machine leaning methods
		Support vector machine				K-nearest neighbor				Random forest
		P	R	F1	ACC	P	R	F1	ACC	P	R	F1	ACC
Female	From 359 to 218	0.88	0.52	0.66	0.95	0.78	0.64	0.70	0.95	0.91	0.83	0.87	0.97
Male	From 359 to 233	0.81	0.57	0.67	0.84	0.76	0.69	0.71	0.85	0.81	0.82	0.82	0.90

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ISSN: 1472-6947

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