PLS Approach for clusterwise linear regression on functional data

[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, (IXth Conference of the International Federation of Classification Societies, Juillet 2004, Chicago)
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.

@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}",
}

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