A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
A Comprehensive Performance Study of Classification of Emotions using EEG Centroid Data
2017
ASIAN JOURNAL OF ENGINEERING
unpublished
Classification of human emotion using EEG signal is an interesting research topic for many. In this paper a detailed study of classification efficiency of different machine learning algorithms using EEG signal was done. The study make use of DEAP data set. The Valance, Arousal and Dominance values reported in DEAP data set were ranked on Mehrabian 3D emotion classification model to produce 8 emotions. k-mean was used to reduce number of observations in original data set and 3, 10 and 40
fatcat:pkwvfpjxdbhsfa3lv5mnmfkbgu