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Sparse Principal Component Analysis (Sparse PCA or SPCA) is an extension of the classic Principal Component Analysis (PCA) used for dimensionality reduction and multivariate data analysis. Its key distinction is that it introduces a sparsity structure to the principal components (PCs) for reasons of simplicity and interpretability. For instance ...
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