KEEL (Knowledge Extraction based on Evolutionary Learning)

KEEL is a software tool to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering, pattern mining and so on. It contains a big collection of classical knowledge extraction algorithms, preprocessing techniques (instance selection, feature selection, discretization, imputation methods for missing values, etc.), Computational Intelligence based learning algorithms, including evolutionary rule learning algorithms based on different approaches (Pittsburgh, Michigan and IRL, ...), and hybrid models such as genetic fuzzy systems, evolutionary neural networks, etc.

It allows us to perform a complete analysis of any learning model in comparison to existing ones, including a statistical test module for comparison. Moreover, KEEL has been designed with a double goal: research and educational.

Licensing

KEEL software is free to downloading and use, but the source code is not directly visible. However, you may ask for the code of a particular algorithm. KEEL may be released under a GPL license in the future.

Links

• KEEL Website %EXT%
• Overview with screenshots %EXT%
• List of well over 100 algorithms implemented by KEEL, with references %EXT%