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dc.contributor.authorLenz, Oliver Urs
dc.contributor.authorCornelis, Chris
dc.contributor.authorPeralta, Daniel
dc.date.accessioned2022-11-18T14:18:14Z
dc.date.available2022-10-23T02:52:32Z
dc.date.available2022-11-18T14:18:14Z
dc.date.issued2022
dc.identifier.issn1544-5615
dc.identifier.otherWOS:000861288500112
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/40607.2
dc.sourceWOS
dc.titleFuzzy-rough-learn 0.2: a Python library for fuzzy rough set algorithms and one-class classification
dc.typeProceedings paper
dc.contributor.imecauthorPeralta, Daniel
dc.contributor.orcidimecPeralta, Daniel::0000-0002-7544-8411
dc.date.embargo9999-12-31
dc.identifier.doi10.1109/FUZZ-IEEE55066.2022.9882778
dc.identifier.eisbn978-1-6654-6710-0
dc.source.numberofpages8
dc.source.peerreviewyes
dc.source.conferenceIEEE 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.conferencedateJUL 18-23, 2022
dc.source.conferencelocationPadua
dc.source.journalna
imec.availabilityPublished - open access
dc.description.wosFundingTextThe research reported in this paper was conducted with the financial support of the Odysseus programme of the Research Foundation -Flanders (FWO).


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