计算机应用与软件Issue(11)：218-220,3.DOI:10.3969/j.issn.1000-386x.2013.11.060
一种基于支持向量机预分类的属性选择算法
AN ATTRIBUTE SELECTION ALGORITHM BASED ON SVM PRE-CLASSIFICATION
摘要
Abstract
Image recognition is generally a problem of high-dimensional classification , so usually it inevitably contains a lot of redundant attributes.Aiming at image recognition problem , in this paper we propose an attribute selection algorithm which is based on SVM pre -classification.First, we use SVM on original training set to pre-classify for computing the classified hyperplane .Then we select features attribute according to the size of the coefficient of the classified hyperplane .Simulation experiments made on the Corel Image data set show that the proposed algorithm is an effective attributes selection method , it can effectively improve the classification performance of traditional classification algorithm .关键词
图像识别/冗余属性/支持向量机/属性选择Key words
Image recognition/Redundant attributes/Support vector machine ( SVM)/Attribute selection分类
信息技术与安全科学引用本文复制引用
周蓉..一种基于支持向量机预分类的属性选择算法[J].计算机应用与软件,2013,(11):218-220,3.基金项目
四川省教育厅重点科研项目（13ZA0035）。 （）
