Model-Based Co-clustering for Ordinal Data

Julien Jacques; Christophe Biernacki

Conference papers

Model-Based Co-clustering for Ordinal Data

Julien Jacques ^{1, 2} Christophe Biernacki ^{3, 2}

1 ERIC - Entrepôts, Représentation et Ingénierie des Connaissances

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

3 LPP - Laboratoire Paul Painlevé - UMR 8524

Abstract : A model-based coclustering algorithm for ordinal data is presented. This algorithm relies on the latent block model using the BOS model (Biernacki and Jacques, 2015, Stat. Comput.) for ordinal data and a SEM-Gibbs algorithm for inference. Numerical experiments on simulated data illustrate the efficiency of the inference strategy.

Document type :

Conference papers

Domain :

Statistics [stat] / Methodology [stat.ME]

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https://hal.archives-ouvertes.fr/hal-01420648
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Submitted on : Thursday, December 22, 2016 - 3:03:26 PM
Last modification on : Friday, April 15, 2022 - 3:00:04 PM

Model-Based Co-clustering for Ordinal Data

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Model-Based Co-clustering for Ordinal Data

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368

77