关键词: 分形维数, 多目标遗传算法, 特征选择

Abstract: In text categorization system, the characteristics of the advantages and disadvantages often greatly affect the design of classifier and performance. A feature subset selection algorithm is presented based on fractal dimension and with elitist strategy of fast non-dominated sorting genetic algorithm. In the algorithm, fractal dimension is used as an evaluation mechanism and NSGA-II algorithm will regard feature subset selection problem as a multi-objective optimization problem to deal with. In order to analyze the validity of the results, the SVM algorithm is utilized to test Fudan University Corpus. The experimental results show that this method has good performance, it can effectively remove the invalid character and improve classification accuracy.

Key words: fractal dimension, multi-objective genetic algorithm, feature selection