TABLE 2.

The performance of the different classifiers.

Classifiers	Accuracy (%)	Precision (%)	Recall (%)	F-score (%)	AUC
Fine tree	80.7	83.5	79.5	81.5	0.85
Medium tree	76.3	81.4	74.5	77.8	0.82
Coarse tree	72.5	78.3	70.8	74.4	0.76
Linear discriminant	78.7	75.8	81.1	78.3	0.87
Quadratic discriminant	63.4	98.4	58.3	73.2	0.89
Logistic regression	80.5	80.3	81.1	80.7	0.88
Linear SVM	80.0	79.2	81.1	80.1	0.88
Quadratic SVM	89.1	87.1	91.0	89.0	0.96
Cubic SVM	93.9	93.8	94.2	94.0	0.97
Fine Gaussian SVM	93.5	94.6	92.7	93.7	0.98
Medium Gaussian SVM	84.3	80.9	87.3	84.0	0.92
Coarse Gaussian SVM	75.5	77.7	75.0	76.3	0.84
Fine KNN	94.2	94.4	94.2	94.3	0.94
Medium KNN	87.8	89.7	86.9	88.2	0.95
Coarse KNN	77.5	75.9	79.1	77.4	0.85
Cosine KNN	87.2	86.5	88.1	87.3	0.95
Cubic KNN	87.0	88.7	86.1	87.4	0.94
Weighted KNN	92.6	91.8	93.6	92.7	0.98
Boosted trees	82.9	82.8	83.4	83.1	0.92
Bagged trees	90.8	91.9	90.2	91.0	0.97
Subspace discriminant	77.1	75.1	78.9	77.0	0.86
Subspace KNN	93.7	93.7	94.0	93.8	0.98
RUSBoosted trees	77.2	82.6	75.1	78.7	0.85

Bold values indicate the best.