Table 2.

Classification results with CS method for dimensionality reduction.

	ECG Original Centered	CS 2	CS 3	CS 4	CS 5	CS 7	CS 9	CS 10	CS 15	CS 20	CS 25
Fine Tree	83.4	49.4	55.3	58.1	68.6	72.3	71.5	72.4	75.7	77.3	79.8
Medium Tree	71.3	45.3	48.0	49.3	54	52.8	51.6	52.3	52.7	60.6	69.2
Coarse Tree	42.8	32.2	34.4	34.2	36.5	35.2	36.2	36.7	35.9	38.0	40.3
Linear Discriminant	76.3	24.2	33.7	35.2	41.4	47.3	55.3	60.0	69.2	71.6	73.9
Quadratic Discriminant	70.0	34.0	47.5	50.3	63.2	74.1	77.8	82.0	87.6	89.1	89.7
Naive Bayes	47.6	33.4	38.9	40.8	47.2	48.6	47.8	49.1	50.3	50.9	52.2
Kernel Naive Bayes	62.5	45.9	48.8	51.7	62.4	66.1	68.0	68.1	70.5	70.5	71.8
Linear SVM	87.3	29.5	38.9	41.6	54.2	63.2	71.3	75.9	82.8	84.4	85.1
Quadratic SVM	95.1	44.5	54.3	61.7	74.7	85.2	88.9	90.8	93.3	94.2	94.5
Cubic SVM	95.2	42.7	53.0	62.2	75.9	86.6	90.1	91.7	93.4	94.7	94.5
Fine Gaussian SVM	87.4	51.8	62.9	69.5	82.0	86.4	87.8	88.5	88.0	87.6	87.9
Medium Gaussian SVM	92.9	49.8	58.7	65.4	78.0	85.4	87.3	88.6	91.2	92.0	93.0
Coarse Gaussian SVM	79.4	32.8	43.6	45.2	62.1	67.2	69.5	71.8	77.5	79.5	80.9
Fine KNN	93.4	39.1	55.1	64.4	80.7	87.6	89.4	91.0	92.4	93.5	93.7
Medium KNN	90.2	48.7	60.8	67.5	80.6	86.5	87.8	88.4	89.6	90.3	90.8
Coarse KNN	77.6	50.4	57.7	61.5	69.2	73.8	74.9	75.5	76.3	76.6	77.4
Cosine KNN	90.5	29.6	47.1	58.2	73.8	83.2	85.9	86.7	88.3	89.7	90.7
Cubic KNN	90.2	48.8	60.8	67.7	80.3	86.4	87.7	88.5	89.8	90.5	90.8
Weighted KNN	91.4	43.6	59.4	68.2	81.9	88.1	89.3	90.1	91.5	92.1	92.3
Ensemble Boosted Trees	78.3	45.9	49.4	52.2	61.8	66.1	67.5	70.6	69.5	73.8	76.8
Ensemble Bagged Trees	91.8	43.9	59.4	65.6	80.3	85.2	87.1	88.2	89.7	90.2	90.4
Ensemble Subspace Discriminant	76.2	24.3	29.1	31.5	40.0	43.9	45.6	47.0	61.1	64.4	70.3
Ensemble Subspace KNN	94.7	23.3	44.0	49.5	74.2	86.0	89.0	90.3	92.4	93.6	94.0
Ensemble RUSBoosted Trees	71.5	45.3	47.9	49.4	53.9	53.8	52.0	52.5	52.8	60.6	69.3