CONTRIBUTORS WELCOME Generalized Additive Models in Python
Python implementation of the rulefit algorithm
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
Python package for Bayesian Machine Learning with scikit-learn API
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
maximtrp/scikit-posthocs 的主要功能包括：General Machine Learning, 机器学习框架, Machine Learning Packages, Statistical Analysis, Statistics, Statistical Modeling。
maximtrp/scikit-posthocs 的开源替代品包括： dswah/pygam — [CONTRIBUTORS WELCOME] Generalized Additive Models in Python. danielhanchen/hyperlearn — 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old. aksnzhy/xlearn — High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization… amazaspshumik/sklearn-bayes — Python package for Bayesian Machine Learning with scikit-learn API. csinva/imodels — Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). christophm/rulefit — Python implementation of the rulefit algorithm.