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Sparse principal component analysis is a technique used in statistical analysis and, in particular, in the analysis of multivariate data sets. It extends the classic method of principal component analysis (PCA) for the reduction of dimensionality of data by introducing sparsity structures to the input variables.
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References
- ↑ ASA Fellow Announcement (PDF), American Statistical Association, retrieved 2019-05-12
- ↑ Highly Cited Researchers
- ↑ IMS Awards Recipients
