Geodesic
The Huber Functions and Their Application to a Classification Problem
Mathematica Applicanda, Tome 48 (2020) no. 2, pp. 99-114.

Voir la notice de l'article provenant de la source Annales Societatis Mathematicae Polonae Series

In the following paper a classification problem with two multivariate normally distributed classes is considered. The problem is solved in a case of an empirical real situation (a motors data) using the Karhunen-Loeve Transform and classifying functions based on estimators for unknown parameters of a multivariate normal distribution. We consider the maximum likelihood estimator and a robust one. The robust estimator bases on the Huber functions. The corresponding classifying functions (classifiers) are compared using the Leave-One-Out method.
DOI : 10.14708/ma.v48i2.7045
Classification : 62C12, 62P30
Mots-clés : the Huber function, multivariate normal model, robust estimator, classifier, the Karhunen-Loeve Transform 
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Henryk Gacki; Agnieszka Kulawik. The Huber Functions and Their Application to a Classification Problem. Mathematica Applicanda, Tome 48 (2020) no. 2, pp.  99-114. doi : 10.14708/ma.v48i2.7045. http://geodesic.mathdoc.fr/articles/10.14708/ma.v48i2.7045/

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