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Mining for Patterns Based on Contingency Tables by KL-Miner – First Experience

  • Jan Rauch
  • Milan šimůnek
  • Václav Lín
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 9)

Abstract

A new datamining procedure called KL-Miner is presented. The procedure mines for various patterns based on evaluation of two–dimensional contingency tables, including patterns of statistical or information theoretic nature. The procedure is aresult of continued development of the academic system LISp-Miner for KDD.

Keywords

Contingency Table Association Rule Data Matrix Partial Condition Relevant Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  • Jan Rauch
    • 1
    • 3
  • Milan šimůnek
    • 2
    • 4
  • Václav Lín
    • 3
  1. 1.EuroMISE Centrum – CardioUSA
  2. 2.Department of Information TechnologyItaly
  3. 3.Department of Information and Knowledge EngineeringCzech Republic
  4. 4.University of EconomicsLaboratory for Intelligent SystemsPragueCzech Republic

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