robustDA (1.1)

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Robust Mixture Discriminant Analysis.

Robust mixture discriminant analysis (RMDA, Bouveyron & Girard, 2009) allows to build a robust supervised classifier from learning data with label noise. The idea of the proposed method is to confront an unsupervised modeling of the data with the supervised information carried by the labels of the learning data in order to detect inconsistencies. The method is able afterward to build a robust classifier taking into account the detected inconsistencies into the labels.

Maintainer: Charles Bouveyron
Author(s): Charles Bouveyron & Stephane Girard

License: GPL-2

Uses: Does not use any package

Released over 5 years ago.

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