Package: parboost
Title: Distributed Model-Based Boosting
Version: 0.1.4
Date: 2015-05-03
Description: Distributed gradient boosting based on the mboost package. The
    parboost package is designed to scale up component-wise functional
    gradient boosting in a distributed memory environment by splitting the
    observations into disjoint subsets, or alternatively using bootstrap
    samples (bagging). Each cluster node then fits a boosting model to its
    subset of the data. These boosting models are combined in an ensemble,
    either with equal weights, or by fitting a (penalized) regression
    model on the predictions of the individual models on the complete
    data.
Author: Ronert Obst <ronert.obst@gmail.com>
Maintainer: Ronert Obst <ronert.obst@gmail.com>
Depends: R (>= 3.0.1), parallel, mboost, party, iterators
Imports: plyr, caret, glmnet, doParallel
License: GPL-2
NeedsCompilation: no
Packaged: 2015-05-03 16:27:09 UTC; ronert
Repository: CRAN
Date/Publication: 2015-05-04 01:24:31
