modAL: A modular active learning framework for Python. modAL is a modular active learning framework for Python, aimed to make active learning research and practice simpler. Its distinguishing features are (i) clear and modular object oriented design (ii) full compatibility with scikit-learn models and workflows. These features make fast prototyping and easy extensibility possible, aiding the development of real-life active learning pipelines and novel algorithms as well. modAL is fully open source, hosted on GitHub at this https URL. To assure code quality, extensive unit tests are provided and continuous integration is applied. In addition, a detailed documentation with several tutorials are also available for ease of use. The framework is available in PyPI and distributed under the MIT license.
Keywords for this software
References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Paul Scherer, Thomas Gaudelet, Alison Pouplin, Suraj M S, Jyothish Soman, Lindsay Edwards, Jake P. Taylor-King: PyRelationAL: A Library for Active Learning Research and Development (2022) arXiv
- Christopher Schröder, Lydia Müller, Andreas Niekler, Martin Potthast: Small-text: Active Learning for Text Classification in Python (2021) arXiv
- Tivadar Danka, Peter Horvath: modAL: A modular active learning framework for Python (2018) arXiv