A Novel Emotion Recognition Method Based on Ensemble Learning and Rough Set Theory

Abstract

Emotion recognition is a very hot topic, which is related with computer science, psychology, artificial intelligence, etc. It is always performed on facial or audio information with classical method such as ANN, fuzzy set, SVM, HMM, etc. Ensemble learning theory is a novelty in machine learning and ensemble method is proved an effective pattern recognition method. In this paper, a novel ensemble learning method is proposed, which is based on selective ensemble feature selection and rough set theory. This method can meet the tradeoff between accuracy and diversity of base classifiers. Moreover, the proposed method is taken as an emotion recognition method and proved to be effective according to the simulation experiments.