An Investigation of Ensemble Methods to Classify Electroencephalogram Signaling Modes

Abstract

This research focuses on the feasibility of synthetic algorithms, including Boosted Trees, Bagged Trees, Subspace KNN, Subspace Discriminant, RUSBoosted Trees for identifying brain wave signal patterns. With two datasets used, it is the one that measures the four types of human emotions (valence, arousal, dominance, like). The receiver consists of 11 states composed of the groups of facial, normal, and thinking signals. The research focuses on researching the above algorithms, using the wavelet transform to determine the signal's characteristics, then classifying, comparing the results, improving, and reaching a conclusion.