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Table 1 Results of performance metrics for valence 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 sSVM54.5355.5292.9169.27
LR56.5057.4283.8168.17
DT52.9855.9369.4061.97
KNN53.9057.9362.1259.95
LDA55.0064.4865.7765.30
15 to 30 sSVM63.3463.3410077.67
LR62.1763.4296.6776.60
DT64.0664.063100%78.09
KNN55.5563.6771.2167.24
LDA57.3467.7269.7968.72
30 to 45 sSVM63.4363.4310077.62
LR63.1264.0596.6777.05
DT61.6064.8610078.09
KNN70.4170.2093.2383.91
LDA56.2567.8766.0567.05
45 to 60 sSVM63.5963.3599.5077.73
LR63.1264.0596.6777.05
DT64.6064.6610078.09
KNN57.6864.0477.4970.11
LDA56.2568.8564.1866.34