Evolving Classifiers ‒ Evolutionary Algorithms in Data Mining

Authors

Abstract

Data mining means to summarize information from large amounts of raw data. It is one of the key technologies in many areas of economy, science, administration and the internet. In this report we introduce an approach for utilizing evolutionary algorithms to breed fuzzy classifier systems. This approach was exercised as part of a structured procedure by the students Achler, Göb, and Voigtmann as contribution to the 2006 Data-Mining-Cup contest, yielding encouragingly positive results.

Keywords

Data Mining, Genetic Algorithms, GAs, Bit Strings, Binary Search Space, Pitt-Style LCSs, Rule-based Classification

BibTeX

@techreport{WAGVZ2007DMC,
  author                    = {Thomas Weise and Stefan Achler and Martin G{\"{o}}b and Christian Voigtmann and Michael Zapf},
  title                     = {{Evolving Classifiers {--} Evolutionary Algorithms in Data Mining}},
  institution               = {{University of Kassel, Fachbereich 16: Elektrotechnik/Informatik: {Kassel, Hesse, Germany}}},
  type                      = {Kasseler Informatikschriften (KIS)},
  number                    = {2007, 4},
  pages                     = {1--20},
  year                      = {2007},
  month                     = sep # {~28, },
  url                       = {http://www.it-weise.de/documents/files/WAGVZ2007DMC.pdf},
  key                       = {WAGVZ2007DMC},
},

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