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Methodology of Application

  • Oded Maimon
  • Mark Last
Chapter
Part of the Massive Computing book series (MACO, volume 1)

Abstract

As mentioned in Chapter 1 above, the goal of the information-theoretic methodology, presented in this book, is to automate the entire process of knowledge discovery. Though this is a first attempt to create a unified framework for most KDD stages, we are far from providing a “turn-key” solution to such a complex problem as building models of knowledge from data. The information-theoretic techniques, presented here, and their results (in the form of networks, rules, predictions, etc.) are just a part of a larger process, which is aimed at identifying and solving business problems.

Keywords

Dimensionality Reduction Target Attribute Input Attribute Nominal Attribute Data Mining Algorithm 
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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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Oded Maimon
    • 1
  • Mark Last
    • 2
  1. 1.Tel-Aviv UniversityTel-AvivIsrael
  2. 2.University of South FloridaTampaUSA

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