organization within 'The Linux Foundation'. With this package, user can create a

Title: Performs boosting algorithms for a binary response
Author: Mark Culp, Kjell Johnson, and George Michailidis
Description: Performs discrete, real, and gentle boost under both exponential and
logistic loss on a given data set.  The package ada provides a straightforward,
well-documented, and broad boosting routine for classification, ideally suited
for small to moderate-sized data sets.  Please refer to the Url below for more
Packaged: Fri Sep 29 11:20:24 2006; culpm

Title: ada: an R package for stochastic boosting
Description: Performs discrete, real, and gentle boost under both
exponential and logistic loss on a given data set.  The package
ada provides a straightforward, well-documented, and broad
boosting routine for classification, ideally suited for small
to moderate-sized data sets.  Please refer to the Url below for

Title: The R Package Ada for Stochastic Boosting

Title: Adaptive Huber Estimation and Regression
Description: Huber-type estimation for mean, covariance and (regularized) regression. For all the methods, the robustification parameter tau is chosen by a tuning-free principle.

Package: adabag
Title: Applies Adaboost.M1 and Bagging
Version: 1.0
Author: Esteban Alfaro Cort�s, Mat�as G�mez Mart�nez y Noelia Garc�a Rubio
Maintainer: Esteban Alfaro Cort�s <Esteban.Alfaro@uclm.es>
Depends: R, rpart
Suggests: mlbench
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.
License: GPL version 2 o newer
Packaged: Thu Jun  1 18:51:35 2006; ealfaro

Package: adabag
Title: Applies Adaboost.M1 and Bagging
Version: 1.1
Author: Esteban Alfaro Cortes, Matias Gamez Martinez and Noelia Garcia Rubio
Maintainer: Esteban Alfaro Cortes <Esteban.Alfaro@uclm.es>
Depends:  R (>= 2.4.0), rpart, mlbench
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.
License: GPL (>= 2)
Packaged: Thu Oct 25 11:12:42 2007; Esteban.Alfaro