Distributed gradient boosting based on the mboost package. The parboost package is designed to scale up componentwise 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.
Package details 


Author  Ronert Obst <ronert.obst@gmail.com> 
Date of publication  20150504 01:24:31 
Maintainer  Ronert Obst <ronert.obst@gmail.com> 
License  GPL2 
Version  0.1.4 
Package repository  View on CRAN 
Installation 
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