"THE ONE CLAUSE AT A TIME (OCAT)
APPROACH TO DATA MINING AND KNOWLEDGE DISCOVERY"
by Evangelos Triantaphyllou
Data Mining and Knowledge Discovery Approaches Based on Rule
Induction Techniques,
(E. Triantaphyllou and G. Felici, Editors), Springer,
Heidelberg, Germany, Chapter 2, pp. 45-87, (2005).
Abstract:
This chapter reviews a data mining and knowledge discovery approach
called OCAT (for One Clause At a Time). The OCAT approach is based
on concepts of mathematical logic and discrete optimization. As
input it uses samples of the performance of the system (or phenomenon)
under consideration and then it extracts its underlying behavior in
terms of a compact and rather accurate set of classification rules.
This chapter also provides ways for decomposing large scale data
mining problems, and a way of how to generate the next best example
to consider for training. The later methods can be combined with any
Boolean function learning method and are not restricted to the OCAT
approach only.
Keywords and Phrases:
Inductive Inference, Knowledge Discovery, Data Mining,
Rule Extraction, Learning from Examples, CNF/DNF, Boolean
Functions, Discrete Optimization, Maximum Clique,
Connected Components in Graphs, Machine Learning.
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