OPFython: A Python implementation for Optimum-Path Forest

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...

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Bibliographic Details
Published inSoftware impacts Vol. 9; p. 100113
Main Authors de Rosa, Gustavo H., Papa, João P.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2021
Subjects
Artificial intelligence
Machine learning
Optimum-Path Forest
Python
Artificial intelligence
Machine learning
Optimum-Path Forest
Python
Online AccessGet full text
ISSN2665-9638
2665-9638
DOI10.1016/j.simpa.2021.100113

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Summary: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. •Python-based open-source Optimum-Path Forest framework.•OPFython implements the same structured proposed by LibOPF.•Composed of pre-defined classes and methods that allows faster prototyping.•Allows usage of modern programming paradigms, such as object-oriented and JSON input data.
ISSN:2665-9638
2665-9638
DOI:10.1016/j.simpa.2021.100113