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[PS04] PLS Approach for clusterwise linear regression on functional data
Conférence Internationale avec comité de lecture : Classification, Clustering and Data Mining Applications, D.Banks et al. editors,, January 2004, pp.167-176,
motcle:
Résumé:
Partial Least Squares approach is used for the clusterwise linear regression algorithm when the set of predictor variables forms a L2 continuous stochastic process.The number of clusters is treated as unknown and the convergence of the clusterwise algorithm is discussed.The approach is compared with other methods via an application on stock-exchange data.
Commentaires:
IXth Conference of the International Federation of Classification Societies, Juillet 2004, Chicago
BibTeX
| @inproceedings { | |||
| PS04, | |||
| title | = | "{PLS Approach for clusterwise linear regression on functional data}", | |
| author | = | " C. Preda and G. Saporta ", | |
| booktitle | = | "{ Classification, Clustering and Data Mining Applications, D.Banks et al. editors,}", | |
| year | = | 2004, | |
| month | = | "January", | |
| pages | = | "167-176", | |
| note | = | "{IXth Conference of the International Federation of Classification Societies, Juillet 2004, Chicago}", | |
| } | |||
