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Séance MA5 - Arbres, analyse de regroupement et méthodes basées sur les rangs pour problèmes complexes / Tree, Clustering and Rank Based Methods for Complex Problems

Jour lundi, le 04 mai 2009
Salle Ordre des CGA
Président Denis Larocque

Présentations

10h30-
10h55
Mixed Effects Regression Trees for Clustered Data
  Ahlem Hajjem, HEC Montreal, Management Sciences

We propose a new regression tree method that can handle unbalanced clusters, allows observations within a cluster to be in different nodes, and can incorporate random effects and observation-level covariates. Simulation results show that it can provide substantial improvements over standard tree algorithms.


10h55-
11h20
Trees and Ensemble Methods Applied to Multiple Outcomes with Mixture of Categorical and Continuous Responses
  Abdessamad Dine, HEC Montréal

We proposed in the past a multivariate tree-based method for multiple outcomes with a mixture of categorical and continuous responses. In this presentation we compare the predictive performance of random forests built using the multivariate tree method and random forests built for each outcome individually. An illustration of the application of this new method is also given.


11h20-
11h45
Élaboration d’une nouvelle méthode de classification avec informations partielles sur la variable cible
  Tarek Grichi, HEC Montreal, Management Sciences

La situation est la suivante. Nous disposons d’un échantillon où la valeur de la variable cible Y est connue pour uniquement une partie des observations. Plus précisément, la variable Y est binaire et seulement la classe ‘1’ est observée. Le but est de scorer la valeur de Y des autres observations de l’échantillon.


11h45-
12h10
Multivariate Nonparametric Methods for Clustered Data
  Denis Larocque, GERAD, HEC Montréal, Méthodes quantitatives de gestion, Canada

During the last decade, there has been a wide interest to extend univariate and multivariate nonparametric procedures based on signs and ranks to clustered and hierarchical data. In this talk, I will present a review of these developments but the main focus will be on the more recent developments using the spatial signs and ranks.


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