RLScore: Regularized Least-Squares Learners

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dc.contributor.authorTapio Pahikkala
dc.contributor.authorAntti Airola
dc.contributor.organizationfi=tietojenkäsittelytiede|en=Computer Science|
dc.contributor.organization-code1.2.246.10.2458963.20.23479734818
dc.converis.publication-id17896921
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/17896921
dc.date.accessioned2022-10-27T12:20:14Z
dc.date.available2022-10-27T12:20:14Z
dc.description.abstract<p>RLScore is a Python open source module for kernel based machine learning. The library provides implementations of several regularized least-squares (RLS) type of learners. RLS methods for regression and classification, ranking, greedy feature selection, multi-task and zero-shot learning, and unsupervised classification are included. Matrix algebra based computational short-cuts are used to ensure efficiency of both training and cross-validation. A simple API and extensive tutorials allow for easy use of RLScore.<br /></p>
dc.format.pagerange1
dc.format.pagerange5
dc.identifier.eissn1533-7928
dc.identifier.jour-issn1532-4435
dc.identifier.olddbid174819
dc.identifier.oldhandle10024/157913
dc.identifier.urihttps://www.utupub.fi/handle/11111/34955
dc.identifier.urlhttp://www.jmlr.org/papers/v17/16-470.html
dc.identifier.urnURN:NBN:fi-fe2021042715977
dc.language.isoen
dc.okm.affiliatedauthorPahikkala, Tapio
dc.okm.affiliatedauthorAirola, Antti
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherMIT Press
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.ispartofjournalJournal of Machine Learning Research
dc.relation.volume17
dc.source.identifierhttps://www.utupub.fi/handle/10024/157913
dc.titleRLScore: Regularized Least-Squares Learners
dc.year.issued2016

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