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OPFython: A Python implementation for Optimum-Path Forest

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Author(s):
de Rosa, Gustavo H. ; Papa, Joao P.
Total Authors: 2
Document type: Journal article
Source: SOFTWARE IMPACTS; v. 9, p. 3-pg., 2021-08-01.
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. (AU)

FAPESP's process: 19/02205-5 - Adversarial learning in natural language processing
Grantee:Gustavo Henrique de Rosa
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 20/12101-0 - Support for computational environments and experiments execution: data acquisition, categorization and maintenance
Grantee:Leandro Aparecido Passos Junior
Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
Grantee:Fabio Gagliardi Cozman
Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC