{"repo":"dswah/pyGAM","free":true,"listed":false,"github":"https://github.com/dswah/pyGAM","clone":"git clone https://github.com/dswah/pyGAM.git","description":"[CONTRIBUTORS WELCOME] Generalized Additive Models in Python","language":"Python","stars":1011,"topics":["machine-learning","data-science","scientific-computing","python","interpretable-machine-learning","gams","explainable-ai","explainable-ml","interpretable-ai","interpretable-ml"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"pyGAM Generalized Additive Models in Python. :rocket: Version 0.12.0 out now! See release notes here. pyGAM is a package for building Generalized Additive Models in Python, with an emphasis on modularity and performance. The API is designed for users of scikit-learn or scipy . Documentation · Tutorials · Medium article --- --- Open Source Community CI/CD Code Downloads ) Citation Documentation - Official pyGAM Documentation: Read the Docs - Building interpretable models with Generalized additive models in Python Installation Acceleration Most of pyGAM's computations are linear algebra operations. To speed up optimization on large models with constraints, it helps to have intel MKL installed. It is currently a bit tricky to install a Numpy linked to the MKL routines with Conda because you have to be careful with which channel you are using. Pip's Numpy-MKL is outdated. An alternative is to use a third-party build: Contributing - HELP REQUESTED Contributions are most welcome! You can help pyGAM in many ways including: - Working on a known bug. - Trying it out and reporting bugs or what was difficult. - Helping improve the documentation. - Writing new distributions, and link functions. - If you need some ideas, please take a look at the issues. To start: - fork the project and cut a new branch - install pygam , editable with developer dependencies (in a new python environment) Make some changes and write a test... - Test your contribution (eg from the .../pyGAM ): - When yo","default_branch":null,"files":null,"tree":[],"storefront":"/r/dswah","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/dswah/pyGAM/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}