Abstract: For solving classification problems,Choquet integral classifier plays an increasingly important role by its nonlinear and nonadditivity.Especially,in the domain of solving the problem of data classification and fusion,Choquet integral has obvious advantages,because its signed fuzzy measure provides an effective representation to describe the intera-ction among contributions from predictive attributes to objective attributes.However,there is lack of an effective me-thod to extract the signed fuzzy measure of Choquet integral.Currently,the most common used method is genetic algorithm,but the genetic algorithm is complex and time-consuming.Since the values of signed fuzzy measure are critical parameters in the Choquet integral classifier,it is necessary to design an efficient extraction method.Based on linear discriminant analysis,this paper proposed an extraction method for retrieving the values of signed fuzzy measure in the Choquet integralbased on linear discriminant analysis,and derived the analytic expression of the signed measure value in Choquet integral under the classification problem,so that the key parameters can be obtained quickly and efficiently.This method was tested and validated on artificial data sets and benchmark data sets,respectively.The experiment results show that this method can effectively solve the optimization problem of signed fuzzy measure in Choquet integral classifier.

Key words: Choquet integral, Classifier, Fuzzy measure, Linear discriminant analysis