Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/10529
Title: Discovering a taste for the unusual: exceptional models for preference mining
Authors: de Sa,CR
Knobbe,A
Carlos Manuel Soares
Alípio Jorge
Paulo Jorge Azevedo
Duivesteijn,W
Issue Date: 2018
Abstract: Exceptional preferences mining (EPM) is a crossover between two subfields of data mining: local pattern mining and preference learning. EPM can be seen as a local pattern mining task that finds subsets of observations where some preference relations between labels significantly deviate from the norm. It is a variant of subgroup discovery, with rankings of labels as the target concept. We employ several quality measures that highlight subgroups featuring exceptional preferences, where the focus of what constitutes ‘exceptional’ varies with the quality measure: two measures look for exceptional overall ranking behavior, one measure indicates whether a particular label stands out from the rest, and a fourth measure highlights subgroups with unusual pairwise label ranking behavior. We explore a few datasets and compare with existing techniques. The results confirm that the new task EPM can deliver interesting knowledge. © 2018 The Author(s)
URI: http://repositorio.inesctec.pt/handle/123456789/10529
http://dx.doi.org/10.1007/s10994-018-5743-z
metadata.dc.type: Publication
article
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