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9 repositories · updated 2026-11-07
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1shap / shapA game theoretic approach to explain the output of any machine learning model.Jupyter NotebookMIT · PermissiveInsufficient rank history25,851
2lightgbm-org / LightGBMA fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.C++MIT · PermissiveInsufficient rank history18,953
3ddbourgin / numpy-mlMachine learning, in numpyPythonGPL-3.0 · Share derivative sourceInsufficient rank history16,323
4EpistasisLab / tpotA Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.Jupyter NotebookLGPL-3.0 · Share derivative sourceInsufficient rank history10,059
5interpretml / interpretFit interpretable models. Explain blackbox machine learning.C++MIT · PermissiveInsufficient rank history6,976
6benedekrozemberczki / awesome-decision-tree-papersA collection of research papers on decision, classification and regression trees with implementations.PythonCC0-1.0 · PermissiveInsufficient rank history2,480
7benedekrozemberczki / awesome-fraud-detection-papersA curated list of data mining papers about fraud detection.PythonCC0-1.0 · PermissiveInsufficient rank history1,841
8benedekrozemberczki / awesome-gradient-boosting-papersA curated list of gradient boosting research papers with implementations.PythonCC0-1.0 · PermissiveInsufficient rank history1,054
9perpetual-ml / perpetualPerpetual is a high-performance gradient boosting machine. It delivers optimal accuracy in a single run without complex tuning through a simple budget parameter. It features out-of-the-box support for causal ML, continual learning, native calibration, and robust drift monitoring, along with Rust core and zero-copy bindings for Python and RRustApache-2.0 · PermissiveInsufficient rank history717
