Emotion recognition can be achieved by obtaining signals from the brain by EEG . This test records the activity of the brain in form of waves. We have used DEAP dataset on which we are classifying the emotion as valance, likeness/dislike, arousal, dominance. We have used LSTM and CNN classifier which gives 88.60 % accuracy to predict the model successfully.
How we got 58560 labels?
On this experiment we have 32 participants 40 one-minute video each one and you avarage the data taking 2sec windows
So i expect 324030)=38400 labels
how did we get the class number as 10 (num_classes = 10) in cell 85. where as we only have binarly class as 0 or 1 in the y_train in cell 75.
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