An augmented Lagrangian approach for sparse principal component analysis
نویسندگان
چکیده
منابع مشابه
An Augmented Lagrangian Approach for Sparse Principal Component Analysis
Principal component analysis (PCA) is a widely used technique for data analysis and dimension reduction with numerous applications in science and engineering. However, the standard PCA suffers from the fact that the principal components (PCs) are usually linear combinations of all the original variables, and it is thus often difficult to interpret the PCs. To alleviate this drawback, various sp...
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Principal component analysis (PCA) is widely used in data processing and dimensionality reduction. However, PCA suffers from the fact that each principal component is a linear combination of all the original variables, thus it is often difficult to interpret the results. We introduce a new method called sparse principal component analysis (SPCA) using the lasso (elastic net) to produce modified...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2011
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-011-0452-4