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主成分分析

于 2021-03-26 发布
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说明:  核主成分分析方法是将主成分分析方法与核方法的有机融合,核心思想是通过引入核方法将输入空间的数据映射到特征空间,并在特征空间进行主成分分析,实现降维与提取非线性数据特征的双重目标。(The kernel principal component analysis (KPCA) is an organic fusion of principal component analysis (PCA) and kernel method. The core idea is to map the data from input space to feature space by introducing the kernel method, and carry out principal component analysis in feature space, so as to achieve the dual goals of dimensionality reduction and feature extraction of nonlinear data.)

文件列表:

主成分分析\hezhuchengfenfenxi.m, 8625 , 2021-03-13
主成分分析\zhuchegnfenfenxi.m, 820 , 2021-03-06
主成分分析\zhuchengfenfenxi.m, 8153 , 2021-03-13

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