特征选择是当前信息领域,尤其是模式识别领域的研究热点.本文从不同角度对特征选择算法进行分类,概述特征选择技术发展的各个分支及发展态势,指出理论研究和实际应用中所存在的一些困难和亟待解决的问题.然后从算法实用性角度出发,结合机器学习的观点,探讨应用支持向量机技术进行特征选择的研究发展思路.
Feature selection is a hot topic in current information science , especially in the field of pattern recognition. In this paper, feature selection algorithms are classified from different points of view. Several embranchments of feature selection and the development situation are introduced. Some difficulties in the theoretic analysis and application are involved. From a practicality angle, using support vector machine to select features is considered as the research direction in machine learning.