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Data Mining with Scatter Search

  • Conference paper
Computer Aided Systems Theory – EUROCAST 2005 (EUROCAST 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3643))

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Abstract

Most Data Mining tasks are performed by the application of Machine Learning techniques. Metaheuristic approaches are becoming very useful for designing efficient tools in Machine Learning. Metaheuristics are general strategies to design efficient heuristic procedures. Scatter Search is a recent metaheuristic that has been successfully applied to solve standard problems in three central paradigms of Machine Learning: Clustering, Classification and Feature Selection. We describe the main components of the Scatter Search metaheuristic and the characteristics of the specific designs to be applied to solve standard problems in these tasks.

This research has been partially supported by the Ministerio de Ciencia y Teconología through the project TIC2002-04242-C03-01; 70% of which are FEDER funds.

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References

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Author information

Authors and Affiliations

  1. Dep. de Estadística, I.O. y Computación, Universidad de La Laguna, 38271, La Laguna, Spain

    I. J. García del Amo, M. García Torres, B. Melián Batista, J. A. Moreno Pérez, J. M. Moreno Vega & Raquel Rivero Martín

Authors
  1. I. J. García del Amo
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  2. M. García Torres
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  3. B. Melián Batista
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  4. J. A. Moreno Pérez
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  5. J. M. Moreno Vega
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  6. Raquel Rivero Martín
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Editor information

Editors and Affiliations

  1. Instituto Universitario de Ciencias y Tecnologícas Cibernéticas, Universidad de Las Palmas de Gran Canaria, Campus de Tafira, 35017, Las Palmas de Gran Canaria,, Las Palmas, Spain

    Roberto Moreno Díaz

  2. Systems Theory, Johannes Kepler University Linz, Altenbergerstrasse 69, A-4040, Linz, Austria

    Franz Pichler

  3. Universidad de Las Palmas de Gran Canaria, Instituto Universitario de Ciencias y Tecnologícas Cibernéticas, Campus de Tafira, 35017, Las Palmas de Gran Canaria, Las Palmas, Spain

    Alexis Quesada Arencibia

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© 2005 Springer-Verlag Berlin Heidelberg

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del Amo, I.J.G., Torres, M.G., Batista, B.M., Pérez, J.A.M., Vega, J.M.M., Martín, R.R. (2005). Data Mining with Scatter Search. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2005. EUROCAST 2005. Lecture Notes in Computer Science, vol 3643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556985_25

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  • DOI: https://doi.org/10.1007/11556985_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29002-5

  • Online ISBN: 978-3-540-31829-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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