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PAKDD
1999
ACM
87views Data Mining» more  PAKDD 1999»
14 years 3 months ago
On Information-Theoretic Measures of Attribute Importance
Abstract. An attribute is deemed important in data mining if it partitions the database such that previously unknown regularities are observable. Many information-theoretic measure...
Yiyu Yao, S. K. Michael Wong, Cory J. Butz
PAKDD
1999
ACM
149views Data Mining» more  PAKDD 1999»
14 years 3 months ago
An Analysis of Quantitative Measures Associated with Rules
In this paper, we analyze quantitative measures associated with if-then type rules. Basic quantities are identified and many existing measures are examined using the basic quantit...
Yiyu Yao, Ning Zhong
PAKDD
1999
ACM
113views Data Mining» more  PAKDD 1999»
14 years 3 months ago
Characterization of Default Knowledge in Ripple Down Rules Method
Abstract. \Ripple Down Rules (RDR)" Method is one of the promising approaches to directly acquire and encode knowledge from human experts. It requires data to be supplied incr...
Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Tak...
PAKDD
1999
ACM
124views Data Mining» more  PAKDD 1999»
14 years 3 months ago
Discovery of Equations and the Shared Operational Semantics in Distributed Autonomous Databases
Empirical equations are an important class of regularities that can be discovered in databases. In this paper we concentrate on the role of equations as de nitions of attribute val...
Zbigniew W. Ras, Jan M. Zytkow
PAKDD
1999
ACM
129views Data Mining» more  PAKDD 1999»
14 years 3 months ago
Visually Aided Exploration of Interesting Association Rules
Association rules are a class of important regularities in databases. They are found to be very useful in practical applications. However, the number of association rules discovere...
Bing Liu, Wynne Hsu, Ke Wang, Shu Chen
PAKDD
1999
ACM
91views Data Mining» more  PAKDD 1999»
14 years 3 months ago
Probing Knowledge in Distributed Data Mining
Yike Guo, Janjao Sutiwaraphun