摘要
利用支持向量机进行模式分类时,特征选择是数据预处理的一项重要内容。有效的特征选择在很大程度上影响着分类器的性能。根据样本各特征分量的均值与方差对分类的影响,提出根据分类权值进行特征选择,以提高支持向量机性能的简便方法,制定了两个具体实施方案。在三个常用数据集上进行了仿真实验,结果验证了方法的有效性。
Feature selection is an important content of data preprocessing in pattern recognition based on SVM.The valid feature selection affects the performance of classification machine to a large extent.According to the effect of the mean and the square difference of each feature of samples,a simple and convenient feature selection method based on the values of classification power is presented,and two concrete schemes are introduced to improve the performance of support vector machine.Three experiments on common datasets confirm the usefulness of the method.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第3期183-185,共3页
Computer Engineering and Applications
关键词
支持向量机
特征选择
分类权
Support Vector Machine（SVM）
feature selection
classification power
