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ordinalClust: a package for analyzing ordinal data

Margot Selosse 1 Julien Jacques 1 Christophe Biernacki 2
2 MODAL - MOdel for Data Analysis and Learning
LPP - Laboratoire Paul Painlevé - UMR 8524, Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694, Polytech Lille - École polytechnique universitaire de Lille
Abstract : Ordinal data are used in a lot of domains, especially when measurements are collected from persons by observations, testings, or questionnaires. ordinalClust is an R package dedicated to ordinal data that proposes tools for modeling, clustering, co-clustering and classification. Ordinal data are modeled by the BOS distribution, which is a meaningful model parametrized by a position and a precision parameter. On one hand, the co-clustering framework uses the Latent Block Model (LBM) and an SEM-Gibbs algorithm for the parameters inference. On the other hand, the clustering and the classification methods follow on from simplified versions of this algorithm. An overview of these methods is given, and the way of using them with the ordinalClust package is described through real datasets.
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https://hal.inria.fr/hal-01678800
Contributor : Margot Selosse <>
Submitted on : Tuesday, January 9, 2018 - 1:50:30 PM
Last modification on : Tuesday, September 22, 2020 - 10:00:03 AM
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  • HAL Id : hal-01678800, version 1

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Margot Selosse, Julien Jacques, Christophe Biernacki. ordinalClust: a package for analyzing ordinal data. 2018. ⟨hal-01678800v1⟩

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