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Using partial least squares regression for conjoint analysis

Giorgio Russolillo 1 Gilbert Saporta 1
1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : After a presentation of the classical methodology of conjoint analysis we advocate the use of PLS regression instead of classical regression in order to obtain a better accuracy in the estimation of utilities. PLS regression provides also interesting graphical representations allowing quick and easy interpretation of the relations among preferences, attributes and profiles.
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Submitted on : Thursday, September 17, 2020 - 9:44:34 AM
Last modification on : Monday, February 21, 2022 - 3:38:18 PM
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Giorgio Russolillo, Gilbert Saporta. Using partial least squares regression for conjoint analysis. Statistica Applicata - Italian Journal of Applied Statistics, Associazione per la Statistica Applicata, 2020, Conjoint Analysis and Decision Making, 32, pp.67-84. ⟨10.26398/IJAS.0032-005⟩. ⟨hal-02941462⟩

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