RapidMiner
'''RapidMiner''' (formerly YALE (Yet Another Learning Environment)) is an environment for [[machine learning]] and [[data mining]] experiments. It allows experiments to be made up of a large number of arbitrarily nestable operators, described in [[XML]] files which can easily be created with RapidMiner's [[graphical user interface]]. Applications of RapidMiner cover both research and real-world data mining tasks.

The initial version has been developed by the Artificial Intelligence Unit of [[Dortmund University of Technology|University of Dortmund]] since [[2001]]. It is distributed under a [[GNU]] license, and has been hosted by [[SourceForge]] since [[2004]].

RapidMiner provides more than 400 operators for all main machine learning procedures, including input and output, and data preprocessing and visualization. It is written in the [[Java (programming language)|Java programming language]] and therefore can work on all popular operating systems. It also integrates all learning schemes and attribute evaluators of the [[Weka (machine learning)|Weka]] learning environment.

== Properties ==
<!-- Deleted image removed: [[Image:Yale andrews curves.gif|thumb|A RapidMiner screenshot (click for full size view).|200px|right]] -->

Some properties of RapidMiner are:
* written in Java
* [[knowledge discovery]] processes are modeled as operator trees
* internal XML representation ensures standardized interchange format of data mining experiments
* scripting language allows for automatic large-scale experiments
* multi-layered data view concept ensures efficient and transparent data handling
* [[graphical user interface]], [[command line]] mode ([[Batch file|batch mode]]), and [[Java API]] for using RapidMiner from your own programs
* [[plugin]] and [[Extension (computing)|extension]] mechanisms, several plugins already exist
* [[plotting]] facility offering a large set of high-dimensional visualization schemes for data and models
* applications include [[text mining]], multimedia mining, feature engineering, data stream mining and tracking drifting concepts, development of ensemble methods, and distributed data mining.

== References ==
* [[Ingo Mierswa|Mierswa, Ingo]] and [[Michael Wurst|Wurst, Michael]] and [[Ralf Klinkenberg|Klinkenberg, Ralf]] and [[Martin Scholz|Scholz, Martin]] and [[Timm Euler|Euler, Timm]]: ''YALE: Rapid Prototyping for Complex Data Mining Tasks'', in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-06), 2006.

== External links ==
* [http://RapidMiner.com/ RapidMiner project home page]
* [http://rapid-i.com/content/view/64/74/lang,en/ YALE becomes RapidMiner]
* [http://sourceforge.net/projects/yale RapidMiner SourceForge.net (SF.net) project site]
* [http://rapid-i.com Rapid-I], the company behind RapidMiner, providing professional services for RapidMiner users

[[Category:Free application software]]
[[Category:Free science software]]
[[Category:Free software projects]]
[[Category:SourceForge projects]]
[[Category:Machine learning]]
[[Category:Artificial intelligence]]
[[Category:Data mining]]