print

print.wsrf

the index of a specific tree.  If missing, <code>print</code>
      will print a summary of the model.

trees

Optional additional arguments. At present no additional
  arguments are used.

Print a summary of the forest model or one specific tree in the forest model
  built from <code>wsrf</code>.

A parallel implementation of Weighted Subspace Random
    Forest.  The Weighted Subspace Random Forest algorithm was
    proposed in the International Journal of Data Warehousing and
    Mining, 8(2):44-63, 2012, proposed by Baoxun Xu, Joshua Zhexue
    Huang, Graham Williams, Qiang Wang, and Yunming Ye.  The algorithm
    can classify very high-dimensional data with random forests built
    using small subspaces.  A novel variable weighting method is used
    for variable subspace selection in place of the traditional random
    variable sampling.This new approach is particularly useful in
    building models from high-dimensional data.

print.wsrf: Print Method for `wsrf` model

Description

Usage

Arguments

See Also