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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Knowledge Discovery through Symbolic Regression with HeuristicLab
verfasst von : Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham, Andreas Scheibenpflug, Michael Affenzeller
Erschienen in: Machine Learning and Knowledge Discovery in Databases
Verlag: Springer Berlin Heidelberg
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This contribution describes how symbolic regression can be used for knowledge discovery with the open-source software HeuristicLab. HeuristicLab includes a large set of algorithms and problems for combinatorial optimization and for regression and classification, including symbolic regression with genetic programming. It provides a rich GUI to analyze and compare algorithms and identified models. This contribution mainly focuses on specific aspects of symbolic regression that are unique to HeuristicLab, in particular, the identification of relevant variables and model simplification.