[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}", |
| } | |