Table 4.

Final results.

Dataset	Algorithm	Positive	Neutral	Negative	Average
GSR_SEL	RF	90.00	83.57	79.29	84.29
	MCC,BAG,RF	89.29	85.00	80.71	85.00
	ASC,RF	90.00	83.57	79.29	84.29
	AB,RF	92.14	85.00	83.57	86.90
	MCC,AB,RF	91.43	85.00	81.43	85.95
GSR_SEL + HRV_SEL	RF	95.00	89.29	78.57	87.62
	MCC,BAG,RF	94.29	87.86	78.57	86.90
	ASC,RF	95.00	89.29	78.57	87.62
	AB,RF	95.00	91.43	80.71	89.05
	MCC,AB,RF	95.00	91.43	82.86	89.76
GSR_SEL + HRV_SEL + EEG_IND_SEL	RF	78.45	89.66	91.38	86.49
	MCC,BAG,RF	77.59	91.38	92.24	87.07
	ASC,RF	79.31	87.93	88.79	85.34
	AB,RF	80.17	87.93	91.38	86.49
	MCC,AB,RF	78.45	87.07	93.10	86.21

Classifiers applied to the best datasets using only the features selected previously. Percentage of positive, neutral, negative and average results for the instances classified correctly.

Bold values indicate the best performance obtained in each test and highlight the optimal combination of features for each dataset.