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» On Objective Measures of Rule Surprisingness
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PKDD
1998
Springer
113views Data Mining» more  PKDD 1998»
13 years 9 months ago
On Objective Measures of Rule Surprisingness
Most of the literature argues that surprisingness is an inherently subjective aspect of the discovered knowledge, which cannot be measured in objective terms. This paper departs fr...
Alex Alves Freitas
PKDD
2005
Springer
94views Data Mining» more  PKDD 2005»
13 years 11 months ago
Evaluating the Correlation Between Objective Rule Interestingness Measures and Real Human Interest
In the last few years, the data mining community has proposed a number of objective rule interestingness measures to select the most interesting rules, out of a large set of discov...
Deborah R. Carvalho, Alex Alves Freitas, Nelson F....
HAIS
2009
Springer
13 years 3 months ago
A Three-Objective Evolutionary Approach to Generate Mamdani Fuzzy Rule-Based Systems
Abstract. In the last years, several papers have proposed to adopt multiobjective evolutionary algorithms (MOEAs) to generate Mamdani fuzzy rulebased systems with different trade-o...
Michela Antonelli, Pietro Ducange, Beatrice Lazzer...
AIA
2007
13 years 6 months ago
Evaluating generalized association rules through objective measures
Generalized association rules are rules that contain some background knowledge, therefore, giving a more general view of the domain. This knowledge is codified by a taxonomy set ...
Veronica Oliveira de Carvalho, Solange Oliveira Re...
SAC
2010
ACM
13 years 5 days ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane