Proceedings of the Korean Information Science Society Conference (한국정보과학회:학술대회논문집)
- 2001.04b
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- Pages.529-531
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- 2001
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- 1598-5164(pISSN)
New EM algorithm for Principal Component Analysis
주성분 분석을 위한 새로운 EM 알고리듬
Abstract
We present an expectation-maximization algorithm for principal component analysis via orthogonalization. The algorithm finds actual principal components, whereas previously proposed EM algorithms can only find principal subspace. New algorithm is simple and more efficient thant probabilistic PCA specially in noiseless cases. Conventional PCA needs computation of inverse of the covariance matrices, which makes the algorithm prohibitively expensive when the dimensions of data space is large. This EM algorithm is very powerful for high dimensional data when only a few principal components are needed.
Keywords