rminer library

rminer: Data mining using the R tool. 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 and Support Vector Machines.

Author: Paulo Cortez 2015@ University of Minho.

The rminer library is made public available (open source) here:

The package is directly available at CRAN: http://cran.r-project.org/web/packages/rminer/. If needed you can also use one of the CRAN: Comprehensive R Archive Network (CRAN) mirrors.
Instalation instructions (if needed): readme.txt
Documentation pdf file: http://cran.r-project.org/web/packages/rminer/rminer.pdf
rminer tutorial: A tutorial on using the rminer R package for data mining tasks
rminer tutorial R code examples: tutorial.zip

Other rminer demonstration files (warning: some code examples might be outdated and might not work in recent rminer versions):

Code described in [Cortez, 2010]): rminerdemo.zip
NN 2010/2012 Summer school demo: NN2012 demo: nndemo.zip
Springer book chapter (in press) demo: chapterdemo.zip
A student of mine created a GUI system: jrminer

Further information:

If you use this package in your research, please cite this reference [Cortez, 2010]:
- [Cortez, 2010] P. Cortez, Data Mining with Neural Networks and Support Vector Machines using the R/rminer Tool. [©Springer] [pdf] [bib] In P. Perner (Ed.), Advances in Data Mining - Applications and Theoretical Aspects, 10th Industrial Conference on Data Mining, LNAI 6171, Springer, pp. 572-583, Berlin, Germany, July, 2010.
Current version includes R documentation and examples;
This library was used in several Data Mining applications: bank marketing, intensive care medicine, meat and wine quality assessment, civil engineering, forest fires prediction, modeling student performance, time series forecasting, spam e-mail detection, ...

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