Overcoming the ordinal imbalanced data problem by combining data processing and stacked generalizations

Desprez, M Zawada, K Ramp, D

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Field	Value	Language
dc.contributor.author	Desprez, M
dc.contributor.author	Zawada, K
dc.contributor.author	Ramp, D https://orcid.org/0000-0003-3202-9898
dc.date.accessioned	2022-01-26T06:50:56Z
dc.date.available	2022-01-26T06:50:56Z
dc.date.issued	2022-03-15
dc.identifier.citation	Machine Learning with Applications, 2022, 7, pp. 1-9
dc.identifier.issn	2666-8270
dc.identifier.uri	http://hdl.handle.net/10453/153585
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Machine Learning with Applications
dc.relation.isbasedon	10.1016/j.mlwa.2021.100241
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Overcoming the ordinal imbalanced data problem by combining data processing and stacked generalizations
dc.type	Journal Article
utslib.citation.volume	7
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.date.updated	2022-01-26T06:50:54Z
pubs.publication-status	Published
pubs.volume	7

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