Package: adabag
Type: Package
Title: Applies Adaboost.M1 and Bagging
Version: 2.0
Date: 2011-07-18
Author: Esteban Alfaro Cortes, Matias Gamez Martinez and Noelia Garcia
Rubio
Maintainer: Esteban Alfaro Cortes <Esteban.Alfaro@uclm.es>
Depends: 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. 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".
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2011-07-18 09:24:53 UTC; Esteban.Alfaro
Repository: CRAN
Date/Publication: 2011-07-23 13:49:26

Package: adabag
Type: Package
Title: Applies Adaboost.M1 and Bagging
Version: 2.1
Date: 2011-10-21
Author: Esteban Alfaro Cortes, Matias Gamez Martinez and Noelia Garcia
Rubio
Maintainer: Esteban Alfaro Cortes <Esteban.Alfaro@uclm.es>
Depends: 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.  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".
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2011-10-21 09:29:09 UTC; Esteban.Alfaro
Repository: CRAN
Date/Publication: 2011-10-23 10:08:30

Package: adabag
Type: Package
Title: Applies AdaBoost.M1, AdaBoost-SAMME and Bagging
Version: 3.0
Date: 2011-12-22
Author: Alfaro-Cortes, Esteban; Gamez-Martinez, Matias and Garcia-Rubio, Noelia
Maintainer: Esteban Alfaro-Cortes <Esteban.Alfaro@uclm.es>
Depends: 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.
Since version 2.0 a new 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 have been 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.
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2011-12-22 12:00:38 UTC; Esteban.Alfaro
Repository: CRAN
Date/Publication: 2011-12-22 13:37:30