Knowledge discovery through symbolic regression with HeuristicLab

Gabriel Kronberger; Stefan Wagner; Michael Kommenda; Andreas Beham; Andreas Scheibenpflug; Michael Affenzeller

doi:10.1007/978-3-642-33486-3_56

Knowledge discovery through symbolic regression with HeuristicLab

Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham, Andreas Scheibenpflug, Michael Affenzeller

Research Center Hagenberg

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

5 Zitate (Scopus)

Abstract

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.

Originalsprache	Englisch
Titel	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings
Seiten	824-827
Seitenumfang	4
Band	7524
Auflage	PART 2
DOIs	https://doi.org/10.1007/978-3-642-33486-3_56
Publikationsstatus	Veröffentlicht - 2012
Veranstaltung	2012 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2012 - Bristol, Großbritannien/Vereinigtes Königreich Dauer: 24 Sep. 2012 → 28 Sep. 2012

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Nummer	PART 2
Band	7524 LNAI
ISSN (Print)	0302-9743
ISSN (elektronisch)	1611-3349

Konferenz

Konferenz	2012 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2012
Land/Gebiet	Großbritannien/Vereinigtes Königreich
Ort	Bristol
Zeitraum	24.09.2012 → 28.09.2012

Zugriff auf Dokument

10.1007/978-3-642-33486-3_56

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Kronberger, G., Wagner, S., Kommenda, M., Beham, A., Scheibenpflug, A., & Affenzeller, M. (2012). Knowledge discovery through symbolic regression with HeuristicLab. in Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings (PART 2 Aufl., Band 7524, S. 824-827). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 7524 LNAI, Nr. PART 2). https://doi.org/10.1007/978-3-642-33486-3_56

Kronberger, Gabriel ; Wagner, Stefan ; Kommenda, Michael et al. / Knowledge discovery through symbolic regression with HeuristicLab. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings. Band 7524 PART 2. Aufl. 2012. S. 824-827 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Knowledge discovery through symbolic regression with HeuristicLab",

abstract = "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.",

author = "Gabriel Kronberger and Stefan Wagner and Michael Kommenda and Andreas Beham and Andreas Scheibenpflug and Michael Affenzeller",

note = "Copyright: Copyright 2012 Elsevier B.V., All rights reserved.; 2012 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2012 ; Conference date: 24-09-2012 Through 28-09-2012",

year = "2012",

doi = "10.1007/978-3-642-33486-3_56",

language = "English",

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volume = "7524",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings",

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Kronberger, G , Wagner, S, Kommenda, M, Beham, A, Scheibenpflug, A & Affenzeller, M 2012, Knowledge discovery through symbolic regression with HeuristicLab. in Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings. PART 2 Aufl., Bd. 7524, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Nr. PART 2, Bd. 7524 LNAI, S. 824-827, 2012 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2012, Bristol, Großbritannien/Vereinigtes Königreich, 24.09.2012. https://doi.org/10.1007/978-3-642-33486-3_56

Knowledge discovery through symbolic regression with HeuristicLab. / Kronberger, Gabriel ; Wagner, Stefan; Kommenda, Michael et al.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings. Band 7524 PART 2. Aufl. 2012. S. 824-827 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 7524 LNAI, Nr. PART 2).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

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AU - Kommenda, Michael

AU - Beham, Andreas

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PY - 2012

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AB - 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.

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DO - 10.1007/978-3-642-33486-3_56

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SN - 9783642334856

VL - 7524

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings

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Kronberger G , Wagner S, Kommenda M, Beham A, Scheibenpflug A, Affenzeller M. Knowledge discovery through symbolic regression with HeuristicLab. in Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Proceedings. PART 2 Aufl. Band 7524. 2012. S. 824-827. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-33486-3_56

Knowledge discovery through symbolic regression with HeuristicLab

Abstract

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