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adabag (version 2.1)

Applies Adaboost.M1 and Bagging

Description

This package implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging algorithm using classification trees as individual classifiers. Once these classifiers have been trained, they can be used to predict on new data. Also, cross validation predictions can be done. This version 2.0 adds a new function "margins" to calculate the margins for these classifiers. Also a higher flexibility is achieved giving access to the "rpart.control" argument of "rpart".

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Version

Install

install.packages('adabag')

Monthly Downloads

7,513

Version

2.1

License

GPL (>= 2)

Maintainer

Esteban Alfaro

Last Published

October 23rd, 2011

Functions in adabag (2.1)

boosting.cv

Runs v-fold cross validation with Adaboost.M1
predict.boosting

Predicts from a fitted Adaboost.M1 object
adabag-package

Applies Adaboost.M1 and Bagging
bagging

Applies the Bagging algorithm to a data set
predict.bagging

Predicts from a fitted Bagging object
bagging.cv

Runs v-fold cross validation with Bagging
margins

Calculates the margins
adaboost.M1

Applies the Adaboost.M1 algorithm to a data set