The alternating least-squares algorithm for CDPCA

Clustering and Disjoint Principal Component Analysis (CDP CA) is a constrained principal component analysis recently proposed for clustering of objects and partitioning of variables, simultaneously, which we have implemented in R language. In this paper, we deal in detail with the alternating least-...

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Bibliographic Details
Main Author: Macedo, E. (author)
Other Authors: Freitas, A. (author)
Format: bookPart
Language:eng
Published: 2016
Subjects:
Clustering
K-means
Principal component analysis
Online Access:http://hdl.handle.net/10773/15320
Country:Portugal
Oai:oai:ria.ua.pt:10773/15320

Internet

http://hdl.handle.net/10773/15320

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