On coding effects in regularized categorical regression

Abstract : This discussion is a continuation of Tutz and Gertheiss (2016)’s paper, where we focus on the importance of the coding of effects in regularized categorical and ordinal regression. We show that, though that an appropriate regularization is profitable for any coding, the choice of a relevant coding can prevail over the one of the regularization term for revealing structures. We focus on predictors though the issues raised also apply to responses. We illustrate our point on a classic data set.
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Article dans une revue
Statistical Modelling, SAGE Publications, 2016, 16 (3), pp.228-237
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https://hal.archives-ouvertes.fr/hal-01338164
Contributeur : Yves Grandvalet <>
Soumis le : mardi 28 juin 2016 - 09:18:45
Dernière modification le : vendredi 13 octobre 2017 - 17:10:03

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  • HAL Id : hal-01338164, version 1

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Julien Chiquet, Yves Grandvalet, Guillem Rigaill. On coding effects in regularized categorical regression . Statistical Modelling, SAGE Publications, 2016, 16 (3), pp.228-237. 〈hal-01338164〉

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