Green Tsetlin Redefining Efficiency in Tsetlin Machine Frameworks
<|reference_start|>Green Tsetlin Redefining Efficiency in Tsetlin Machine Frameworks: Green Tsetlin (GT) is a Tsetlin Machine (TM) framework developed to solve real-world problems using TMs. Several frameworks already exist that provide access to TM implementations. However, these either lack features or have a research-first focus. GT is an easy-to-use framework that aims to lower the complexity and provide a production-ready TM implementation that is great for experienced practitioners and beginners. To this end, GT establishes a clear separation between training and inference. A C++ backend with a Python interface provides competitive training and inference performance, with the option of running in pure Python. It also integrates support for critical components such as exporting trained models, hyper-parameter search, and cross-validation out-of-the-box.<|reference_end|>
@article{glimsdal2024green,
    title={Green Tsetlin Redefining Efficiency in Tsetlin Machine Frameworks},
    author={Sondre Glimsdal, Sebastian {O}stby, Tobias M. Brambo, Eirik M. Vinje},
    journal={arXiv preprint arXiv:2405.04212},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.04212},
    primaryClass={cs.AI cs.LG}
}