Sparse Principal Component Analysis (Sparse PCA) is an extension of traditional Principal Component Analysis (PCA) that seeks to identify a set of principal components that are not only effective in explaining the variance in the data but also exhibit sparse loadings. This means that each principal component is influenced by a limited number of original variables rather than being a linear combination of all variables.
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