Show simple item record

dc.contributor.authorCarmona, C. J.en
dc.contributor.authorElizondo, Daviden
dc.date.accessioned2017-05-31T14:21:12Z
dc.date.available2017-05-31T14:21:12Z
dc.date.issued2016-06-01
dc.identifier.citationCarmona, C.J. and Elizondo, D. (2016) Supervised Descriptive Rule Discovery: A Survey of the State-of-the-Art.en
dc.identifier.urihttp://hdl.handle.net/2086/14217
dc.description.abstractThe supervised descriptive rule discovery concept groups a set of data mining techniques whose objective is to describe data with respect to a property of interest. Among the techniques within this concept are the subgroup discovery, emerging patterns and contrast sets. This contribution presents the supervised descriptive rule discovery concept within the data mining literature. Specifically, it is important to remark the main di erence with respect to other existing techniques within classification or description. In addition, a a survey of the state-of-the-art about the different techniques within supervised descriptive rule discovery throughout the literature can be observed. The paper allows to the experts to analyse the compatibilities between terms and heuristics of the different data mining tasks within this concept.en
dc.language.isoenen
dc.publisherDMUen
dc.subjectRule Discoveryen
dc.subjectData miningen
dc.subjectSubgroup Discoveryen
dc.subjectPatternsen
dc.titleSupervised Descriptive Rule Discovery: A Survey of the State-of-the-Arten
dc.typeTechnical Reporten
dc.researchgroupDIGITSen
dc.peerreviewedNoen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceN/Aen
dc.date.acceptance2016-06-01en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record