H2O-3 is an open-source distributed machine learning platform with tools including deep learning, gradient boosting, and random forests.
Open source
12 alternativesOPFython
A Python-inspired implementation of the Optimum-Path Forest classifier.
About OPFython
OPFython is a Python implementation of the Optimum-Path Forest family of classifiers, distributed as an open-source repository under the Apache License 2.0. It offers supervised, semi-supervised, unsupervised and KNN-supervised models, built on NumPy and Numba, and follows the LibOPF reference implementation. The package is installable with pip or UV and requires Python 3.11 or newer.
Key features
- SupervisedOPF for complete-graph supervised classification
- KNNSupervisedOPF using learned KNN adjacency
- SemiSupervisedOPF learning from labeled and unlabeled samples
- UnsupervisedOPF for density-based clustering and label propagation
- 47 distance metrics, dataset loaders, splitters and LibOPF converters
- Pre-computed distance matrices via pre_computed_distance constructor argument
Best for: Researchers, students and developers who need an open-source Python implementation of Optimum-Path Forest classifiers for experiments or coursework.
Good for
- Open source under the Apache License 2.0
- Cited in published research (Software Impacts, 2021) with a documented citation format
- Accompanied by documentation, examples and application workflows
Watch out for
- Requires Python 3.11 or newer
- Labels must be zero-based and sequential
- KNN models require 1
OPFython at a glance
- Website
- github.com/gugarosa/opfython
- Category
- AI & Machine Learning › AI for Education
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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OPFython FAQ
What Python version does OPFython require?
Python 3.11 or newer.
How is OPFython installed?
With pip using python -m pip install opfython, by adding it to a UV-managed project with uv add opfython, or as an editable source checkout with python -m pip install -e .
What label format do the classifiers expect?
Labels must be zero-based and sequential; features, labels and optional sample indexes must also have matching sample counts, or a SizeError is raised.
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