OPFython: A Python implementation for Optimum-Path Forest[Formula presented]
dc.contributor.author | de Rosa, Gustavo H. [UNESP] | |
dc.contributor.author | Papa, João P. [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.date.accessioned | 2022-05-01T09:30:54Z | |
dc.date.available | 2022-05-01T09:30:54Z | |
dc.date.issued | 2021-08-01 | |
dc.description.abstract | OPFython 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.affiliation | Department of Computing São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01 | |
dc.description.affiliationUnesp | Department of Computing São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01 | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
dc.description.sponsorshipId | FAPESP: #2013/07375-0 | |
dc.description.sponsorshipId | FAPESP: #2014/12236-1 | |
dc.description.sponsorshipId | FAPESP: #2019/02205-5 | |
dc.description.sponsorshipId | FAPESP: #2019/07665-4 | |
dc.description.sponsorshipId | FAPESP: #2020/12101-0 | |
dc.description.sponsorshipId | CNPq: #307066/2017-7 | |
dc.description.sponsorshipId | CNPq: #427968/2018-6 | |
dc.identifier | http://dx.doi.org/10.1016/j.simpa.2021.100113 | |
dc.identifier.citation | Software Impacts, v. 9. | |
dc.identifier.doi | 10.1016/j.simpa.2021.100113 | |
dc.identifier.issn | 2665-9638 | |
dc.identifier.scopus | 2-s2.0-85115882125 | |
dc.identifier.uri | http://hdl.handle.net/11449/233595 | |
dc.language.iso | eng | |
dc.relation.ispartof | Software Impacts | |
dc.source | Scopus | |
dc.subject | Artificial intelligence | |
dc.subject | Machine learning | |
dc.subject | Optimum-Path Forest | |
dc.subject | Python | |
dc.title | OPFython: A Python implementation for Optimum-Path Forest[Formula presented] | en |
dc.type | Artigo | |
unesp.author.orcid | 0000-0002-6442-8343[1] | |
unesp.author.orcid | 0000-0002-6494-7514[2] | |
unesp.campus | Universidade Estadual Paulista (Unesp), Faculdade de Ciências, Bauru | pt |
unesp.department | Computação - FC | pt |