Package: adabag
Type: Package
Title: Applies multiclass AdaBoost.M1, AdaBoost-SAMME and Bagging
Version: 3.1
Date: 2012-06-04
Author: Alfaro-Cortes, Esteban; Gamez-Martinez, Matias and
        Garcia-Rubio, Noelia
Maintainer: Esteban Alfaro-Cortes <Esteban.Alfaro@uclm.es>
Depends: rpart, mlbench, caret
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.  Since version 2.0
        the function "margins" is available to calculate the margins
        for these classifiers.  Also a higher flexibility is achieved
        giving access to the "rpart.control" argument of "rpart".  Four
        important new features were introduced on version 3.0,
        AdaBoost-SAMME (Zhu et al., 2009) is implemented and a new
        function "errorevol" shows the error of the ensembles as a
        function of the number of iterations.  In addition, the
        ensembles can be pruned using the option "newmfinal" in the
        predict.bagging and predict.boosting functions and the
        posterior probability of each class for observations can be
        obtained. Version 3.1 modifies the relative importance measure
        to take into account the gain of the Gini index given by a
        variable in each tree and the weights of these trees.
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2012-07-04 20:22:15 UTC; Esteban.Alfaro
Repository: CRAN
Date/Publication: 2012-07-05 17:18:10
