Sparse Principal Component Analysis with Preserved Sparsity Pattern

Name: Sparse Principal Component Analysis with Preserved Sparsity Pattern
Creator: The University of Western Australia
Published: 2024-12-14T18:08:27+08:00

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稀疏主成分分析

多维数据分析

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资源简介：

MATLAB code + demo to reproduce results for "Sparse Principal Component Analysis with Preserved Sparsity". This code calculates the principal loading vectors for any given high-dimensional data matrix. The advantage of this method over existing sparse-PCA methods is that it can produce principal loading vectors with the same sparsity pattern for any number of principal components. Please see Readme.md for more information.

提供机构：

The University of Western Australia

Sparse Principal Component Analysis with Preserved Sparsity Pattern

资源简介：

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