VORTRAG
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Oesterreichisches Forschungsinstitut fuer Artificial Intelligence(OFAI)
Freyung 6/6, A-1010 Wien
Tel.: +43-1-53361120, Fax: +43-1-5336112-77, Email: sec@oefai.at
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Dr. Roman Rosipal
Oesterreichisches Forschungsinstitut
fuer Artificial Intelligence, OFAI, Wien
OVERVIEW AND SOME ASPECTS OF PARTIAL LEAST SQUARES
Partial least squares (PLS) is a popular approach for soft modeling in
industrial applications. PLS is a method for constructing predictive
models consisting of a set of score vectors (latent variables). The
score vectors are constructed to model relations between multivariate
descriptor and uni- or multivariate response blocks of data where a
criterion of maximal covariance is used. This talk will give an
overview of PLS and its different forms. The nonlinear, kernel-based,
extension of PLS will be considered throughout the talk in parallel to
the linear PLS model. Existing relations of PLS to canonical
correlation analysis, Fisher discriminant analysis and principal
component analysis will be highlighted. The talk will focus on
statistical perspective of the PLS regression model and its shrinkage
properties with respect to ordinary least squares regression. Several
aspects of PLS associated with multiple multivariate response
regression, geometric interpretation, variables selection and the use
of the PLS model in discrimination tasks will also be mentioned in the
talk. Finally, several successful applications of the use of the PLS
regression and classification models on electroencephalogram data will
be described.
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Zeit: Mittwoch, 16. Maerz 2005, 18:30 Uhr pktl.
Ort: Oesterreichisches Forschungsinstitut
fuer Artificial Intelligence, OFAI
Freyung 6, Stiege 6, 1010 Wien.
OESTERREICHISCHES FORSCHUNGSINSTITUT
FUER ARTIFICIAL INTELLIGENCE
o.Univ.-Prof. Ing. Dr. Robert Trappl