OPFython: A Python implementation for Optimum-Path Forest[Formula presented]

dc.contributor.authorde Rosa, Gustavo H. [UNESP]
dc.contributor.authorPapa, João P. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-05-01T09:30:54Z
dc.date.available2022-05-01T09:30:54Z
dc.date.issued2021-08-01
dc.description.abstractOPFython is an open-sourced Python package that implements Optimum-Path Forest algorithms using object-oriented programming and a straightforward structure. It provides an alternative implementation to the standard LibOPF package, which heavily depends on the C language and occasionally hinders fast prototyping. Additionally, OPFython provides documented code, unitary tests, and examples that assist users in learning how to work with the package. Such features are well-suited for researchers and developers interested in exploring alternative state-of-the-art machine learning algorithms.en
dc.description.affiliationDepartment of Computing São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01
dc.description.affiliationUnespDepartment of Computing São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdFAPESP: #2013/07375-0
dc.description.sponsorshipIdFAPESP: #2014/12236-1
dc.description.sponsorshipIdFAPESP: #2019/02205-5
dc.description.sponsorshipIdFAPESP: #2019/07665-4
dc.description.sponsorshipIdFAPESP: #2020/12101-0
dc.description.sponsorshipIdCNPq: #307066/2017-7
dc.description.sponsorshipIdCNPq: #427968/2018-6
dc.identifierhttp://dx.doi.org/10.1016/j.simpa.2021.100113
dc.identifier.citationSoftware Impacts, v. 9.
dc.identifier.doi10.1016/j.simpa.2021.100113
dc.identifier.issn2665-9638
dc.identifier.scopus2-s2.0-85115882125
dc.identifier.urihttp://hdl.handle.net/11449/233595
dc.language.isoeng
dc.relation.ispartofSoftware Impacts
dc.sourceScopus
dc.subjectArtificial intelligence
dc.subjectMachine learning
dc.subjectOptimum-Path Forest
dc.subjectPython
dc.titleOPFython: A Python implementation for Optimum-Path Forest[Formula presented]en
dc.typeArtigo
unesp.author.orcid0000-0002-6442-8343[1]
unesp.author.orcid0000-0002-6494-7514[2]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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