rminer: Data Mining Classification and Regression Methods

Facilitates the use of data mining algorithms in classification and regression (including time series forecasting) tasks by presenting a short and coherent set of functions. Versions: 1.4 - new classification and regression models/algorithms, with a total of 14 classification and 15 regression methods, including: Decision Trees, Neural Networks, Support Vector Machines, Random Forests, Bagging and Boosting; 1.3 and 1.3.1 - new classification and regression metrics (improved mmetric function); 1.2 - new input importance methods (improved Importance function); 1.0 - first version.

Version: 1.4
Depends: kknn
Imports: methods, plotrix, lattice, nnet, pls, MASS, mda, rpart, randomForest, adabag, party, Cubist, kernlab, e1071
Published: 2014-11-07
Author: Paulo Cortez
Maintainer: Paulo Cortez <pcortez at dsi.uminho.pt>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://cran.r-project.org/web/packages/rminer/ http://www3.dsi.uminho.pt/pcortez/rminer.html
NeedsCompilation: no
In views: MachineLearning
CRAN checks: rminer results

Downloads:

Reference manual: rminer.pdf
Package source: rminer_1.4.tar.gz
Windows binaries: r-devel: rminer_1.4.zip, r-release: rminer_1.4.zip, r-oldrel: rminer_1.4.zip
OS X Snow Leopard binaries: r-release: rminer_1.4.tgz, r-oldrel: rminer_1.4.tgz
OS X Mavericks binaries: r-release: rminer_1.4.tgz
Old sources: rminer archive