EFS: Tool for Ensemble Feature Selection

Provides a function to check the importance of a feature based on a dependent classification variable. An ensemble of correlation and importance measure tests are used to determine the normed importance value of all features. Combining these methods in one function (building the sum of the importance values) leads to a better tool for selecting most important features. This selection can also be viewed in a barplot using the barplot_fs() function and proved using an also provided function for a logistic regression model, namely logreg_test().

Version: 1.0.0
Imports: party, pROC, randomForest, ROCR, grDevices, graphics, stats
Published: 2016-08-02
Author: Nikita Genze, Ursula Neumann
Maintainer: Ursula Neumann <u.neumann at wz-straubing.de>
BugReports: NA
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: EFS results


Reference manual: EFS.pdf
Package source: EFS_1.0.0.tar.gz
Windows binaries: r-devel: EFS_1.0.0.zip, r-release: EFS_1.0.0.zip, r-oldrel: EFS_1.0.0.zip
OS X Mavericks binaries: r-release: EFS_1.0.0.tgz, r-oldrel: EFS_1.0.0.tgz