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Table 2 Results of performance metrics for arousal classification

From: A comparative analysis of machine learning methods for emotion recognition using EEG and peripheral physiological signals

TimeClassifierAccuracy (%)Precision (%)Recall (%)F1-score (%)
0 to 15 sSVM56.8656.8698.9172.87
LR59.3359.5295.9573.42
DT55.4857.4983.2468.07
KNN52.9559.9563.1561.05
LDA55.6255.7797.1270.45
15 to 30 sSVM63.3963.8899.5677.87
LR64.5464.5399.2678.19
DT63.3565.1092.7876.38
KNN59.8163.9185.6073.31
LDA63.1263.3299.5077.39
30 to 45 sSVM73.7573.7799.5084.73
LR63.8264.3997.4177.53
DT64.0664.0610078.09
KNN58.8863.7383.0272.11
LDA63.2863.4699.2677.42
45 to 60 sSVM63.5963.6799.5077.66
LR64.8264.4977.0577.95
DT64.5364.4499.9678.26
KNN63.3569.3599.7577.66
LDA63.1263.3299.5077.39