CAJ | 학술논문

在文本分类系统中，特征的优劣往往极大地影响着分类器的设计和性能。提出一种利用分形维数和带精英策略的非劣支配排序遗传算法进行特征选择的方法。在该方法中分形维数作为特征选择的一个评价机制，利用NSGA-II算法将特征子集选择问题视为多目标优化问题来处理。为了分析结果的有效性，利用SVM分类算法对复旦大学语料库进行测试。实验结果表明该方法具有较好的性能，它可以有效去除无效特征并提高分类准确性。
재문본분류계통중，특정적우렬왕왕겁대지영향착분류기적설계화성능。제출일충이용분형유수화대정영책략적비렬지배배서유전산법진행특정선택적방법。재해방법중분형유수작위특정선택적일개평개궤제，이용NSGA-II산법장특정자집선택문제시위다목표우화문제래처리。위료분석결과적유효성，이용SVM분류산법대복단대학어료고진행측시。실험결과표명해방법구유교호적성능，타가이유효거제무효특정병제고분류준학성。
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 prob-lem to deal with. In order to analyze the validity of the results, the SVM algorithm is utilized to test Fudan University Cor-pus. The experimental results show that this method has good performance, it can effectively remove the invalid character and improve classification accuracy.