Ranking objective interestingness measures with sensitivity values

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Ranking objective interestingness measures with sensitivity values

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dc.contributor.author Huỳnh, Xuân Hiệp
dc.contributor.author Fabrice, Guillet
dc.contributor.author Lê, Quyết Thắng
dc.contributor.author Henri, Briand
dc.date.accessioned 2011-04-21T07:50:02Z
dc.date.available 2011-04-21T07:50:02Z
dc.date.issued 2008
dc.identifier.citation VNU Journal of Science, Natural Sciences and Technology 24 (2008) 122-132 vi
dc.identifier.uri http://hdl.handle.net/123456789/1982
dc.description.abstract In this paper, we propose a new approach to evaluate the behavior of objective interestingness measures on association rules. The objective interestingness measures are ranked according to the most significant interestingness interval calculated from an inversely cumulative distribution. The sensitivity values are determined by this interval in observing the rules having the highest interestingness values. The results will help the user (a data analyst) to have an insight view on the behaviors of objective interestingness measures and as a final purpose, to select the hidden knowledge in a rule set or a set of rule sets represented in the form of the most interesting rules. vi
dc.description.sponsorship Quỹ Giáo dục Cao học Hàn Quốc (the Korea Foundation for Advanced Studies) vi
dc.language.iso en vi
dc.subject Knowledge Discovery from Databases (KDD) vi
dc.subject association rules vi
dc.subject sensitivity value vi
dc.subject objective interestingness measures vi
dc.subject interestingness interval vi
dc.title Ranking objective interestingness measures with sensitivity values vi
dc.type Working Paper vi

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