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Author Yamada, Y. ♦ Suzuki, E.
Sponsorship IEEE ♦ IEEE Neural Networks Soc
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2002
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Spirals ♦ Data mining ♦ Knowledge engineering ♦ Machine learning ♦ Production
Abstract We report our preliminary endeavour for spiral discovery of exception rules based on discovered pieces of knowledge. An exception rule, which represents a deviational pattern to a general rule, exhibits unexpectedness and is sometimes extremely useful. We have proposed a domain-independent approach for simultaneous discovery of exception rules and their general rules. Exceptions are always interesting to discoverers, as they challenge the existing knowledge and often lead to the growth of knowledge in new directions. We propose a discovery method which exploits pre-discovered pairs of exception rules and their general rules, and apply it to a benchmark data set in knowledge discovery.
Description Author affiliation: Div. of Electr. & Comput. Eng., Yokohama Nat. Univ., Japan (Yamada, Y.; Suzuki, E.)
ISBN 0780372808
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2002-05-12
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 510.73 kB
Page Count 6
Starting Page 872
Ending Page 877


Source: IEEE Xplore Digital Library