A Combination Classification Method of Multiple Decision Trees Based on Genetic Algorithm

For classification problems in data mining, based on thought of combination classification method, this paper proposes a combination classification method of multiple decision trees based on genetic algorithm. In the proposed combination classification method, multiple decision trees that adopt the method of probability measurement level output are parallel combined. Then genetic algorithm is used for the optimization of connection weight matrix in combination algorithm. Further more, two sets of simulation experiment data are used to test and evaluate the proposed combination classification method. Results of the experiments indicate that the proposed combination classification method has higher classification accuracy level than single decision tree. Moreover, it optimizes classification rules and sustains good interpretability for classification results.