Sparse principal component analysis via axis-aligned random projections
نویسندگان
چکیده
منابع مشابه
Sparse principal component analysis via random projections
We introduce a new method for sparse principal component analysis, based on the aggregation of eigenvector information from carefully-selected random projections of the sample covariance matrix. Unlike most alternative approaches, our algorithm is non-iterative, so is not vulnerable to a bad choice of initialisation. Our theory provides great detail on the statistical and computational trade-of...
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series B (Statistical Methodology)
سال: 2020
ISSN: 1369-7412
DOI: 10.1111/rssb.12360