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.


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install.packages("robustDA")

1.1 by Charles Bouveyron, 4 years ago


Browse source code at https://github.com/cran/robustDA


Authors: Charles Bouveyron & Stephane Girard


Documentation:   PDF Manual  


Task views: Robust Statistical Methods


GPL-2 license


Depends on MASS, mclust, Rsolnp


See at CRAN