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基于PCA的SVM分类

于 2020-06-20 发布 文件大小:77KB
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代码说明:

  选择“BreastCancer”数据集,使用支持向量机(SVM)对其进行分类。作为对比,第一次对特征集直接进行支持向量机分类,第二次对特征集进行主成分分析法的特征提取后,再对特征提取后的特征集进行支持向量机分类。并且对比和分析了两次分类的结果。(The BreastCancer data set is selected and classified by Support Vector Machine (SVM). For comparison, the first time the feature set is classified directly by support vector machine, the second time the feature set is extracted by principal component analysis, and then the feature set is classified by support vector machine. The results of the two classifications are compared and analyzed.)

文件列表:

基于PCA的SVM分类, 0 , 2019-07-31
基于PCA的SVM分类\BreastCancer_data.xlsx, 42899 , 2018-12-07
基于PCA的SVM分类\BreastCancer_PCA_SVM.m, 618 , 2019-01-03
基于PCA的SVM分类\BreastCancer_SVM.m, 185 , 2018-12-07
基于PCA的SVM分类\代码.doc, 30720 , 2019-01-03
基于PCA的SVM分类\分析.docx, 34989 , 2019-01-03

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