wsrf: Weighted Subspace Random Forest for Classification
Version 1.7.13

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 by Baoxun Xu, Joshua Zhexue Huang, Graham Williams, Qiang Wang, and Yunming Ye (2012) . 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.

Browse man pages Browse package API and functions Browse package files

AuthorQinghan Meng [aut], He Zhao [aut, cre], Graham J. Williams [aut], Junchao Lv [aut], Baoxun Xu [aut], Joshua Zhexue Huang [aut]
Date of publication2017-04-17 13:53:47 UTC
MaintainerHe Zhao <Simon.Yansen.Zhao@gmail.com>
LicenseGPL (>= 2)
Version1.7.13
URL https://github.com/SimonYansenZhao/wsrfhttp://togaware.com
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("wsrf")

Man pages

combine.wsrf: Combine Ensembles of Trees
correlation.wsrf: Correlation
importance.wsrf: Extract Variable Importance Measure
oob.error.rate.wsrf: Out-of-Bag Error Rate
predict.wsrf: Predict Method for 'wsrf' Model
print.wsrf: Print Method for 'wsrf' model
strength.wsrf: Strength
subset.wsrf: Subset of a Forest
varCounts.wsrf: Number of Times of Variables Selected as Split Condition
wsrf: Build a Forest of Weighted Subspace Decision Trees

Functions

clwsrf Source code
combine Man page Source code
combine.wsrf Man page Source code
correlation Man page Source code
correlation.wsrf Man page Source code
importance Man page Source code
importance.wsrf Man page Source code
localwsrf Source code
onAttach Source code
oob.error.rate Man page Source code
oob.error.rate.wsrf Man page Source code
predict Man page
predict.wsrf Man page Source code
print Man page
print.wsrf Man page Source code
reduce.wsrf Source code
strength Man page Source code
strength.wsrf Man page Source code
subset Man page
subset.wsrf Man page Source code
varCounts.wsrf Man page Source code
wsrf Man page Source code Source code
wsrf.default Man page Source code
wsrf.formula Man page Source code

Files

inst
inst/CITATION
inst/NEWS.Rd
inst/doc
inst/doc/wsrf-guide.Rmd
inst/doc/wsrf-guide.R
inst/doc/wsrf-guide.html
tests
tests/wsrftest.Rout.save
tests/wsrftest.R
src
src/wsrf.h
src/Makevars
src/rforest.h
src/tree.cpp
src/rforest.cpp
src/node.h
src/c4_5_var_selector.cpp
src/meta_data.cpp
src/utility.h
src/tree.h
src/IGR.h
src/var_selector.h
src/dataset.h
src/c4_5_var_selector.h
src/dataset.cpp
src/IGR.cpp
src/sampling.h
src/sampling.cpp
src/Makevars.win
src/meta_data.h
src/wsrf_init.cpp
src/wsrf.cpp
NAMESPACE
R
R/correlation.wsrf.R
R/varCounts.wsrf.R
R/print.wsrf.R
R/combine.wsrf.R
R/wsrf.default.R
R/strength.wsrf.R
R/subset.wsrf.R
R/oob.error.rate.wsrf.R
R/importance.wsrf.R
R/wsrf.formula.R
R/predict.wsrf.R
R/wsrf.R
vignettes
vignettes/wsrf-guide.Rmd
vignettes/wsrf-guide.bib
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/print.wsrf.Rd
man/combine.wsrf.Rd
man/strength.wsrf.Rd
man/predict.wsrf.Rd
man/correlation.wsrf.Rd
man/subset.wsrf.Rd
man/oob.error.rate.wsrf.Rd
man/importance.wsrf.Rd
man/varCounts.wsrf.Rd
man/wsrf.Rd
wsrf documentation built on May 19, 2017, 11:23 p.m.