parboost (0.1.4)

Distributed Model-Based Boosting.

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.

Maintainer: Ronert Obst
Author(s): Ronert Obst <>

License: GPL-2

Uses: caret, doParallel, glmnet, iterators, mboost, party, plyr

Released over 4 years ago.