Decision trees combination method based on genetic algorithm with application in CRM

For customer classification problems in customer relationship management, this paper proposes a combination classification method of multiple decision trees based on a genetic algorithm. In the combination classification method, multiple decision trees that assign each class a probability value are arranged in parallel. A genetic algorithm is used for the optimization of the connection weight matrix in the combination algorithm. Further, the method is tested and evaluated by a simulation experiment that is conducted with simulation data of customer credit rating assessment. Compared with the single decision tree and other combination methods, the experimental result shows that it improves the classification accuracy and optimizes classification rules, and holds favorable interpretability for classification result at the same time.