Abstract
Emotion recognition is very important for applications of human-computer intelligent interaction. It is always performed on facial or audio information with such method as ANN, fuzzy set, SVM, HMM, etc. Ensemble learning is a hot topic in machine learning and ensemble method is proved an effective pattern recognition method. In this paper, a novel ensemble learning method which is based on selective ensemble feature selection and rough set theory is proposed, and it meets the tradeoff between the 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.
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