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17

ISCI
1998

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A Rough Set Approach to Attribute Generalization in Data Mining

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A Rough Set Approach to Attribute Generalization in Data Mining

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This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification rules from very large data bases generalized by dynamic conceptual hierarchies provided by users. In general, the process of attribute generalization may introduce inconsistency into a generalized relation. This issue is resolved by using the inductive learning algorithm, LERS based on rough set theory. Q 1998 Elsevier Science Inc. All rights reserved.

Chien-Chung Chan

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Dynamic Conceptual Hierarchies | Inductive Learning Algorithm | ISCI 1998 | Large Data Bases |

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Added	22 Dec 2010
Updated	22 Dec 2010
Type	Journal
Year	1998
Where	ISCI
Authors	Chien-Chung Chan

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