A combination classification method of multiple decisions trees-based on generic algorithm towards customer behavior

In order to solve the classification problems of customer behaviors with randomicity and non-conformability, a combination classification method is proposed of multiple decision trees based on genetic algorithm. In this method, multiple decision trees that adopt the method of probability measurement level output are combined in parallel. Genetic algorithm is utilized to optimize connection weight matrix in combination algorithm. Furthermore, two sets of simulation experiment data are used to test and evaluate the proposed method. Results of the experiments indicate that the proposed method generates a higher classification accuracy rate than other methodspsila for customer behavior segmentation.