This paper presents information theory and statistical analysis as two fundamental conceptual tools for data mining. A data mining technique based on these two conceptual tools consists of three steps. The first step is a statistical approach for discovering data patterns. The second step is an information-theoretic approach for identifying models that encapsulate the statistical behavior of the data patterns. The last step is a probabilistic approach for pattern-based inference that uncovers unknown significant event patterns.
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Bon K. Sy (2001) studied this question.
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