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DMKD
1997
ACM
198views Data Mining» more  DMKD 1997»
15 years 5 months ago
Clustering Based On Association Rule Hypergraphs
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
ECAI
2004
Springer
15 years 6 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
DATAMINE
2006
131views more  DATAMINE 2006»
15 years 1 months ago
A systematic approach to the assessment of fuzzy association rules
In order to allow for the analysis of data sets including numerical attributes, several generalizations of association rule mining based on fuzzy sets have been proposed in the li...
Didier Dubois, Eyke Hüllermeier, Henri Prade
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
15 years 5 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...
KDD
1997
ACM
122views Data Mining» more  KDD 1997»
15 years 5 months ago
Computing Optimized Rectilinear Regions for Association Rules
We address the problem of nding useful regions for two-dimensional association rules and decision trees. In a previous paper we presented ecient algorithms for computing optimiz...
Kunikazu Yoda, Takeshi Fukuda, Yasuhiko Morimoto, ...