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. 2016 Jul 15;10:74. doi: 10.3389/fncom.2016.00074

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.