Regression Analysis based on Fuzzy Clustering for Electroencephalogram Data

Abstract

We propose a fuzzy logistic regression model for Electroencephalogram Data. The purpose is to discriminate between kinds of human thinking through the use of Electroencephalogram signals. In our proposed method, we introduce classification structure obtained by fuzzy clustering into the logistic regression model in order to improve the precision of the discrimination. Several numerical examples are demonstrated to show a better performance of our proposed method.