Fuzzy-rough-learn 0.2: a Python library for fuzzy rough set algorithms and one-class classification

dc.contributor.author	Lenz, Oliver Urs
dc.contributor.author	Cornelis, Chris
dc.contributor.author	Peralta, Daniel
dc.contributor.imecauthor	Peralta, Daniel
dc.contributor.orcidimec	Peralta, Daniel::0000-0002-7544-8411
dc.date.accessioned	2022-11-18T14:18:14Z
dc.date.available	2022-10-23T02:52:32Z
dc.date.available	2022-11-18T14:18:14Z
dc.date.embargo	9999-12-31
dc.date.issued	2022
dc.description.wosFundingText	The research reported in this paper was conducted with the financial support of the Odysseus programme of the Research Foundation -Flanders (FWO).
dc.identifier.doi	10.1109/FUZZ-IEEE55066.2022.9882778
dc.identifier.eisbn	978-1-6654-6710-0
dc.identifier.issn	1544-5615
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/40607
dc.publisher	IEEE
dc.source.conference	IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) / IEEE World Congress on Computational Intelligence (IEEE WCCI) / International Joint Conference on Neural Networks (IJCNN) / IEEE Congress on Evolutionary Computation (IEEE CEC)
dc.source.conferencedate	JUL 18-23, 2022
dc.source.conferencelocation	Padua
dc.source.journal	na
dc.source.numberofpages	8
dc.title	Fuzzy-rough-learn 0.2: a Python library for fuzzy rough set algorithms and one-class classification
dc.type	Proceedings paper
dspace.entity.type	Publication
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