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» Mining Positive and Negative Fuzzy Association Rules
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DAWAK
2006
Springer
15 years 1 months ago
Efficient Mining of Dissociation Rules
Abstract. Association rule mining is one of the most popular data mining techniques. Significant work has been done to extend the basic association rule framework to allow for mini...
Mikolaj Morzy
FUZZIEEE
2007
IEEE
15 years 4 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...
APIN
2006
168views more  APIN 2006»
14 years 9 months ago
Utilizing Genetic Algorithms to Optimize Membership Functions for Fuzzy Weighted Association Rules Mining
It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining. In general, it is unre...
Mehmet Kaya, Reda Alhajj
DATAMINE
2006
131views more  DATAMINE 2006»
14 years 9 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
KBS
2006
79views more  KBS 2006»
14 years 9 months ago
Using multiple and negative target rules to make classifiers more understandable
One major goal for data mining is to understand data. Rule based methods are better than other methods in making mining results comprehensible. However, the current rule based cla...
Jiuyong Li, Jason Jones