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Other rminer demonstration files (warning: some code examples might be outdated and might not work in recent rminer versions):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