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Proceedings Paper

Statistical extension of rough set rule induction
Author(s): Shusaku Tsumoto
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Paper Abstract

Rough set based rule induction methods have been applied to knowledge discovery in databases. The empirical results obtained show that they are very powerful and that some important knowledge has been extracted from datasets. However, quantitative evaluation of induced rules are based not on statistical evidence but on rather naive indices, such as conditional probabilities and functions of conditional probabilities. In this paper, we introduce a new approach to induced rules for quantitative evaluation, which can be viewed as a statistical extension of rough set methods. For this extension, chi-square distribution and F- distribution play an important role in statistical evaluation.

Paper Details

Date Published: 27 March 2001
PDF: 9 pages
Proc. SPIE 4384, Data Mining and Knowledge Discovery: Theory, Tools, and Technology III, (27 March 2001); doi: 10.1117/12.421072
Show Author Affiliations
Shusaku Tsumoto, Shimane Medical Univ. (Japan)

Published in SPIE Proceedings Vol. 4384:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology III
Belur V. Dasarathy, Editor(s)

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