Supervised classification using homogeneous logical proportions for binary and nominal features

Moraes, RM; Machado, LS; Prade, H; Richard, G

Supervised classification using homogeneous logical proportions for binary and nominal features

Moraes, RM Machado, LS Prade, H

Richard, G

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 8258 LNCS (PART 1), pp. 165 - 173
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Moraes, RM	en_US
dc.contributor.author	Machado, LS	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.contributor.author	Richard, G	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 8258 LNCS (PART 1), pp. 165 - 173	en_US
dc.identifier.isbn	9783642418211	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32904
dc.description.abstract	The notion of homogeneous logical proportions has been recently introduced in close relation with the idea of analogical proportion. The four homogeneous proportions have intuitive meanings, which can be related with classification tasks. In this paper, we proposed a supervised classification algorithm using homogeneous logical proportions and provide results for all. A final comparison with previous works using similar methodologies and with other classifiers is provided. © Springer-Verlag 2013.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-41822-8_21	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Supervised classification using homogeneous logical proportions for binary and nominal features	en_US
dc.type	Conference Proceeding
utslib.citation.volume	PART 1	en_US
utslib.citation.volume	8258 LNCS	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	PART 1	en_US
pubs.publication-status	Published	en_US
pubs.volume	8258 LNCS	en_US

Abstract:

The notion of homogeneous logical proportions has been recently introduced in close relation with the idea of analogical proportion. The four homogeneous proportions have intuitive meanings, which can be related with classification tasks. In this paper, we proposed a supervised classification algorithm using homogeneous logical proportions and provide results for all. A final comparison with previous works using similar methodologies and with other classifiers is provided. © Springer-Verlag 2013.

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http://hdl.handle.net/10453/32904