The research of the feature selection method based on the ECE and quantum genetic algorithm

Feature selection method is the critical technique of the automatic text categorization. A new method of the text feature selection based on the quantum genetic algorithm is proposed in this paper. First of all, using the ECE statistical method to remove redundant features and noise features for the original feature set, Genetic algorithms are used to optimal feature subset; finally the best feature subset is obtained. In the method, the text vector is coded by quantum bit, and the chromosome is updated by the quantum rotating gate and quantum not-gate. Meanwhile, according to the characteristics of the information filtering, we consider adequately on the feature weight, text similarity and vector dimension in order to improve the fitness function. The experiment has proved that the method can reduce the dimension of text vector and improve the precision of text classification.