Table 3.

Results without DIVA.

Data set	Train acc	Test acc	Balanced acc	Precision	Recall	F1	Auc
Classification and Regression Tree	65.40	61.69	61.44	0.60	0.59	0.59	0.62
Logistic Regression	69.86	60.47	60.37	0.58	0.59	0.58	0.63
Linear Discriminant Analysis	71.55	58.66	58.60	0.56	0.57	0.56	0.60
Artificial Neural Networks	69.11	56.70	59.96	0.56	0.63	0.56	0.65
K Nearest Neighbor	75.80	59.09	59.14	0.57	0.56	0.56	0.61
Support Vector Machine (RBF)	62.74	57.71	58.84	0.60	0.49	0.51	0.66
Support Vector Machine (Linear)	72.50	59.46	59.33	0.57	0.57	0.56	0.61
Gaussian Naïve Bayes	57.35	54.26	55.66	0.51	0.81	0.62	0.61
Random Forest	100.00	58.88	59.61	0.61	0.53	0.51	0.66
Extreme Gradient Boosting	100.00	57.52	57.28	0.54	0.51	0.52	0.63
Averaged	75.43	58.08	58.75	0.57	0.59	0.55	0.63