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SVM-Matlab代码

于 2022-04-19 发布 文件大小:257.03 kB
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应用背景机器学习分类算法,支持向量机SVM,应用于数据分析(线性回归)、分类器开发(二类问题,多类问题,如垃圾邮件分类)。运用支持向量机SVM开发分类器正确率高,平均正确率为90%左右。关键技术包含支持向量机SVM分类算法过程模版、参数优化算法(如pa算法等)、降维算法,机器学习分类算法,支持向量机SVM,应用于数据分析(线性回归)、分类器开发(二类问题,多类问题,如垃圾邮件分类)。运用支持向量机SVM开发分类器正确率高,平均正确率为90%左右。

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