Публікація:
A method for association rule quality evaluation based on information theory

dc.contributor.authorSitnikov, D.
dc.contributor.authorTitova, O.
dc.contributor.authorRyabov, O.
dc.date.accessioned2018-06-04T18:46:56Z
dc.date.available2018-06-04T18:46:56Z
dc.date.issued2006
dc.description.abstractThe concept of patterns representing functional, logical and other dependencies in data lies in the basis of the Data Mining technology. One of the wide spread forms for representing discovered knowledge patterns is association rules. A method for evaluating an association rule from the viewpoint of information theory has been suggested, which allows us to calculate a generalized characteristic of associations (based on mutual information) with the help of the well known association rule parameters: Support, Confidence and Improvement. Using such a characteristic of associations complements the traditional association parameters and allows setting a linear order on the set of associations, which is useful for evaluating and filtering obtained dependencies. Besides we have carried out analysis of the dependence of the association rule self-descriptiveness on the standard parameters.uk_UA
dc.identifier.citationSitnikov D. A method for association rule quality evaluation based on information theory / D. Sitnikov, O. Titova, O. Ryabov // WIT Transactions on Information and Communication Technologies. – 2006. – V. 37. – P. 25-34.uk_UA
dc.identifier.urihttp://openarchive.nure.ua/handle/document/5787
dc.language.isoenuk_UA
dc.publisherWIT Transactions on Information and Communication Technologiesuk_UA
dc.subjectassociation rulesuk_UA
dc.subjectdata mininguk_UA
dc.subjectparameter estimationuk_UA
dc.titleA method for association rule quality evaluation based on information theoryuk_UA
dc.typeArticleuk_UA
dspace.entity.typePublication

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