Worst-case analysis of rule discovery

Einoshin Suzuki

doi:10.1007/3-540-45650-3_31

Worst-case analysis of rule discovery

Einoshin Suzuki

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

In this paper, we perform a worst-case analysis of rule discovery. A rule is defined as a probabilistic constraint of true assignment to the class attribute of corresponding examples. In data mining, a rule can be considered as representing an important class of discovered patterns. We accomplish the aforementioned objective by extending a preliminary version of PAC learning, which represents a worst-case analysis for classification. Our analysis consists of two cases: the case in which we try to avoid finding a bad rule, and the case in which we try to avoid overlooking a good rule. Discussions on related works are also provided for PAC learning, multiple comparison, analysis of association rule discovery, and simultaneous reliability evaluation of a discovered rule.

Original language	English
Title of host publication	Discovery Science - 4th International Conference, DS 2001, Proceedings
Editors	Klaus P. Jantke, Ayumi Shinohara
Publisher	Springer Verlag
Pages	365-377
Number of pages	13
ISBN (Print)	9783540429562
DOIs	https://doi.org/10.1007/3-540-45650-3_31
Publication status	Published - 2001
Externally published	Yes
Event	4th International Conference on Discovery Science, DS 2001 - Washington, United States Duration: Nov 25 2001 → Nov 28 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2226
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Conference on Discovery Science, DS 2001
Country/Territory	United States
City	Washington
Period	11/25/01 → 11/28/01

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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10.1007/3-540-45650-3_31

Cite this

Suzuki, E. (2001). Worst-case analysis of rule discovery. In K. P. Jantke, & A. Shinohara (Eds.), Discovery Science - 4th International Conference, DS 2001, Proceedings (pp. 365-377). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2226). Springer Verlag. https://doi.org/10.1007/3-540-45650-3_31

Worst-case analysis of rule discovery. / Suzuki, Einoshin.
Discovery Science - 4th International Conference, DS 2001, Proceedings. ed. / Klaus P. Jantke; Ayumi Shinohara. Springer Verlag, 2001. p. 365-377 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2226).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Suzuki, E 2001, Worst-case analysis of rule discovery. in KP Jantke & A Shinohara (eds), Discovery Science - 4th International Conference, DS 2001, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2226, Springer Verlag, pp. 365-377, 4th International Conference on Discovery Science, DS 2001, Washington, United States, 11/25/01. https://doi.org/10.1007/3-540-45650-3_31

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Worst-case analysis of rule discovery

Abstract

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All Science Journal Classification (ASJC) codes

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