rminer: Simpler use of data mining methods (e.g. NN and SVM) in classification and regression

This package facilitates the use of data mining algorithms in classification and regression tasks by presenting a short and coherent set of functions. While several DM algorithms can be used, it is particularly suited for Neural Networks (NN) and Support Vector Machines (SVM). Versions: 1.3.1 minor corrections; 1.3 - new classification and regression metrics (improved mmetric function); 1.2 - new input importance methods (improved Importance function); 1.1 - minor error corrections; 1.0 - first version.

Version: 1.3.1
Imports: nnet, kknn, kernlab, rpart, plotrix, lattice, methods
Suggests: randomForest, MASS, mda
Published: 2013-08-12
Author: Paulo Cortez
Maintainer: Paulo Cortez <pcortez at dsi.uminho.pt>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www3.dsi.uminho.pt/pcortez/rminer.html
NeedsCompilation: no
In views: MachineLearning
CRAN checks: rminer results


Reference manual: rminer.pdf
Package source: rminer_1.3.1.tar.gz
Windows binaries: r-devel: rminer_1.3.1.zip, r-release: rminer_1.3.1.zip, r-oldrel: rminer_1.3.1.zip
OS X Snow Leopard binaries: r-release: rminer_1.3.1.tgz, r-oldrel: rminer_1.3.1.tgz
OS X Mavericks binaries: r-release: rminer_1.3.1.tgz
Old sources: rminer archive