2010, ISBN: 9783843356954

[ED: Taschenbuch / Paperback], [PU: LAP Lambert Academic Publishing], Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, a… Mehr…

[ED: Taschenbuch / Paperback], [PU: LAP Lambert Academic Publishing], Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, applied scientists routinely use PLS for classification and there is substantial empirical evidence to suggest that it performs well in that role. The interesting question is "why?" Why can a procedure that is principally designed for over-determined regression problems locate and emphasize group structure? Using PLS in this manner has heuristic support owing to the relationship between PLS and canonical correlations analysis (CCA) and the relationship, in turn, between CCA and linear discriminant analysis (LDA). This dissertation replaces the heuristics with a formal statistical explanation. As a consequence, it will become clear that PLS is to be preferred over principal components analysis (PCA) when discrimination is the goal and dimension reduction is needed., DE, [SC: 0.00], Neuware, gewerbliches Angebot, H: 220mm, B: 150mm, T: 5mm, 96, [GW: 144g], Selbstabholung und Barzahlung, PayPal, offene Rechnung, Banküberweisung, Internationaler Versand<

ISBN: 3843356955

[EAN: 9783843356954], Neubuch, Publisher/Verlag: LAP Lambert Academic Publishing | Statistical Theory and Implementation | Partial least squares (PLS) was not originally designed as a too… Mehr…

[EAN: 9783843356954], Neubuch, Publisher/Verlag: LAP Lambert Academic Publishing | Statistical Theory and Implementation | Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, applied scientists routinely use PLS for classification and there is substantial empirical evidence to suggest that it performs well in that role. The interesting question is "why?" Why can a procedure that is principally designed for over-determined regression problems locate and emphasize group structure? Using PLS in this manner has heuristic support owing to the relationship between PLS and canonical correlations analysis (CCA) and the relationship, in turn, between CCA and linear discriminant analysis (LDA). This dissertation replaces the heuristics with a formal statistical explanation. As a consequence, it will become clear that PLS is to be preferred over principal components analysis (PCA) when discrimination is the goal and dimension reduction is needed. | Format: Paperback | Language/Sprache: english | 144 gr | 220x150x5 mm | 96 pp<

2010, ISBN: 3843356955

[EAN: 9783843356954], Neubuch, [PU: LAP Lambert Acad. Publ. Okt 2010], Neuware - Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite… Mehr…

[EAN: 9783843356954], Neubuch, [PU: LAP Lambert Acad. Publ. Okt 2010], Neuware - Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, applied scientists routinely use PLS for classification and there is substantial empirical evidence to suggest that it performs well in that role. The interesting question is 'why ' Why can a procedure that is principally designed for over-determined regression problems locate and emphasize group structure Using PLS in this manner has heuristic support owing to the relationship between PLS and canonical correlations analysis (CCA) and the relationship, in turn, between CCA and linear discriminant analysis (LDA). This dissertation replaces the heuristics with a formal statistical explanation. As a consequence, it will become clear that PLS is to be preferred over principal components analysis (PCA) when discrimination is the goal and dimension reduction is needed. 96 pp. Englisch<

2010, ISBN: 3843356955

[EAN: 9783843356954], Neubuch, [PU: LAP Lambert Acad. Publ. Okt 2010], Neuware - Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite… Mehr…

[EAN: 9783843356954], Neubuch, [PU: LAP Lambert Acad. Publ. Okt 2010], Neuware - Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, applied scientists routinely use PLS for classification and there is substantial empirical evidence to suggest that it performs well in that role. The interesting question is 'why ' Why can a procedure that is principally designed for over-determined regression problems locate and emphasize group structure Using PLS in this manner has heuristic support owing to the relationship between PLS and canonical correlations analysis (CCA) and the relationship, in turn, between CCA and linear discriminant analysis (LDA). This dissertation replaces the heuristics with a formal statistical explanation. As a consequence, it will become clear that PLS is to be preferred over principal components analysis (PCA) when discrimination is the goal and dimension reduction is needed. 96 pp. Englisch<

2010, ISBN: 3843356955

Kartoniert / Broschiert, mit Schutzumschlag 11, [PU:LAP LAMBERT Academic Publishing]