bagRboostR is a set of ensemble classifiers for multinomial classification. The bagging function is the implementation of Breiman's ensemble as described by Opitz & Maclin (1999). The boosting function is the implementation of Stagewise Additive Modeling using a Multi-class Exponential loss function (SAMME) created by Zhu et al (2006). Both bagging and SAMME implementations use randomForest as the weak classifier and expect a character outcome variable. Each ensemble classifier returns a character vector of predictions for the test set.

Documentation

Manual: bagRboostR.pdf
Vignette: None available.

Maintainer: Shannon Rush <shannonmrush at gmail.com>

Author(s): Shannon Rush <shannonmrush at gmail.com>

Install package and any missing dependencies by running this line in your R console:

install.packages("bagRboostR")

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Imports randomForest
Suggests testthat
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Package bagRboostR
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Version 0.0.2
Published 2014-03-05
License MIT + file LICENSE
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NeedsCompilation no
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Package source bagRboostR_0.0.2.tar.gz