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wsrf (version 1.4.0)
Weighted Subspace Random Forest
Description
The wsrf package is a parallel implementation of the
Weighted Subspace Random Forest algorithm proposed (wsrf). A
novel variable weighting method is used for variable subspace
selection in place of the traditional approach of random
variable sampling. This new approach is particularly useful
in building models for high dimensional data---often
consisting of thousands of variables. Parallel computation is
used to take advantage of multi-core machines and clusters of
machines to build random forest models from high dimensional
data with reduced elapsed times.