Nothing
Robust mixture discriminant analysis (RMDA), proposed in Bouveyron & Girard, 2009 <doi:10.1016/j.patcog.2009.03.027>, 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.
Package details |
|
---|---|
Author | Charles Bouveyron & Stephane Girard |
Maintainer | Charles Bouveyron <charles.bouveyron@gmail.com> |
License | GPL-2 |
Version | 1.2 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.