parboost: 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.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=parboost
to link to this page.