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<dc:title xml:lang="fr">Effets masqués en analyse prédictive</dc:title>
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<dc:subject xml:lang="fr">Effets d'âge</dc:subject>
<dc:subject xml:lang="fr">Effets de cohorte</dc:subject>
<dc:subject xml:lang="fr">Effets de marge</dc:subject>
<dc:subject xml:lang="fr">Support vector machines</dc:subject>
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<dc:subject xml:lang="en">Age effects</dc:subject>
<dc:subject xml:lang="en">Cohort effect</dc:subject>
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<dcterms:abstract xml:lang="fr">L’objectif de cette thèse consiste en l’élaboration de deux méthodologies visant à révéler des effets jusqu’alors masqués en modélisation décisionnelle. Dans la première partie, nous cherchons à mettre en œuvre une méthode d’analyse locale des critères de choix dans un contexte de choix binaires. Dans une seconde partie, nous mettons en avant les effets de génération dans l’étude des comportements de choix. Dans les deux parties, notre démarche de recherche combine de nouveaux outils d’analyse prédictive (Support Vector Machines, FANOVA, PLS) aux outils traditionnels de statistique inférentielle, afin d’enrichir les résultats habituels par des informations complémentaires sur les effets masqués que constituent les effets locaux dans les fonctions de choix binaires, et les effets de génération dans l’analyse temporelle des comportement de choix. Les méthodologies proposées, respectivement nommées AEL et APC-PLS, sont appliquées sur des cas réels, afin d’en illustrer le fonctionnement et la pertinence.</dcterms:abstract>
<dcterms:abstract xml:lang="en">The objective of this thesis is the development of two methodologies to reveal previously hidden effects in decision modeling. In the first part, we try to implement a method of local analysis in order to select criteria in the context of binary choices. In a second part, we highlight the effects of generations in the study of consumer behavior. In both parts, our research approach combines new predictive analytical tools (such as Support Vector Machines, FANOVA, PLS) to traditional tools of inferential statistics, to enrich the usual results by additional on the masked effects, which are the local effects in the binary choice functions, and the effects of generation in temporal choice behavior analysis.The proposed methodologies, respectively named AEL and APC- PLS are both applied to real cases in order to illustrate their operation and relevance.</dcterms:abstract>
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