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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| Formato: | bookPart |
| Idioma: | eng |
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2016
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| Texto completo: | http://hdl.handle.net/10773/15320 |
| País: | Portugal |
| Oai: | oai:ria.ua.pt:10773/15320 |