Article

Genetic programming for attribute construction in data mining

Authors:

Fernando E. B. Otero,

Monique M. S. Silva,

Alex A. Freitas,

Julio C. NievolaAuthors Info & Claims

EuroGP'03: Proceedings of the 6th European conference on Genetic programming

Pages 384 - 393

Published: 14 April 2003 Publication History

Abstract

For a given data set, its set of attributes defines its data space representation. The quality of a data space representation is one of the most important factors influencing the performance of a data mining algorithm. The attributes defining the data space can be inadequate, making it difficult to discover high-quality knowledge. In order to solve this problem, this paper proposes a Genetic Programming algorithm developed for attribute construction. This algorithm constructs new attributes out of the original attributes of the data set, performing an important preprocessing step for the subsequent application of a data mining algorithm.

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Cited By

Gonçalves EFreitas APlastino A(2018)A Survey of Genetic Algorithms for Multi-Label Classification2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477927(1-8)Online publication date: 8-Jul-2018
https://dl.acm.org/doi/10.1109/CEC.2018.8477927
Yazdani SShanbehzadeh JHadavandi E(2017)MBCGP-FEKnowledge-Based Systems10.1016/j.knosys.2017.08.005135:C(89-98)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.knosys.2017.08.005
Torrano-Gimenez CNguyen HAlvarez GFranke K(2015)Combining expert knowledge with automatic feature extraction for reliable web attack detectionSecurity and Communication Networks10.1002/sec.6038:16(2750-2767)Online publication date: 10-Nov-2015
https://dl.acm.org/doi/10.1002/sec.603
Show More Cited By

Genetic programming for attribute construction in data mining
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
2. Information systems
  1. Information systems applications

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Information & Contributors

Information

Published In

cover image Guide Proceedings

EuroGP'03: Proceedings of the 6th European conference on Genetic programming

April 2003

486 pages

ISBN:354000971X

Editors:
Conor Ryan
University of Limerick, Computer Science and Information Systems, Limerick, Ireland
,
Terence Soule
University of Idaho, Department of Computer Science, Moscow, ID
,
Maarten Keijzer
Free University of Amsterdam, Department of Computer Science, Amsterdam, The Netherlands
,
Edward Tsang
University of Essex, Department of Computer Science, Colchester, United Kingdom
,
Riccardo Poli
University of Essex, Department of Computer Science, Colchester, United Kingdom

Sponsors

University of Essex
EvoNet

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 14 April 2003

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Cited By

Gonçalves EFreitas APlastino A(2018)A Survey of Genetic Algorithms for Multi-Label Classification2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477927(1-8)Online publication date: 8-Jul-2018
https://dl.acm.org/doi/10.1109/CEC.2018.8477927
Yazdani SShanbehzadeh JHadavandi E(2017)MBCGP-FEKnowledge-Based Systems10.1016/j.knosys.2017.08.005135:C(89-98)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.knosys.2017.08.005
Torrano-Gimenez CNguyen HAlvarez GFranke K(2015)Combining expert knowledge with automatic feature extraction for reliable web attack detectionSecurity and Communication Networks10.1002/sec.6038:16(2750-2767)Online publication date: 10-Nov-2015
https://dl.acm.org/doi/10.1002/sec.603
Xue BZhang MDai YBrowne WAlba E(2013)PSO for feature construction and binary classificationProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463376(137-144)Online publication date: 6-Jul-2013
https://dl.acm.org/doi/10.1145/2463372.2463376
Can BHeavey C(2012)A comparison of genetic programming and artificial neural networks in metamodeling of discrete-event simulation modelsComputers and Operations Research10.1016/j.cor.2011.05.00439:2(424-436)Online publication date: 1-Feb-2012
https://dl.acm.org/doi/10.1016/j.cor.2011.05.004
Alfred RAmran IBeng LFun T(2012)Unsupervised learning of mutagenesis molecules structure based on an evolutionary-based features selection in DARAProceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence10.1007/978-3-642-35101-3_25(291-299)Online publication date: 4-Dec-2012
https://dl.acm.org/doi/10.1007/978-3-642-35101-3_25
Icke IRosenberg A(2011)Multi-objective genetic programming for visual analyticsProceedings of the 14th European conference on Genetic programming10.5555/2008307.2008337(322-334)Online publication date: 27-Apr-2011
https://dl.acm.org/doi/10.5555/2008307.2008337
Can BHeavey C(2011)Comparison of experimental designs for simulation-based symbolic regression of manufacturing systemsComputers and Industrial Engineering10.1016/j.cie.2011.03.01261:3(447-462)Online publication date: 1-Oct-2011
https://dl.acm.org/doi/10.1016/j.cie.2011.03.012
Shafti LPérez E(2009)Evolutionary multi-feature construction for data reductionApplied Soft Computing10.1016/j.asoc.2009.04.0039:4(1296-1303)Online publication date: 1-Sep-2009
https://dl.acm.org/doi/10.1016/j.asoc.2009.04.003
Neshatian KZhang M(2008)Genetic programming and class-wise orthogonal transformation for dimension reduction in classification problemsProceedings of the 11th European conference on Genetic programming10.5555/1792694.1792716(242-253)Online publication date: 26-Mar-2008
https://dl.acm.org/doi/10.5555/1792694.1792716
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