Linked pages
- GitHub - slundberg/shap: A game theoretic approach to explain the output of any machine learning model. https://github.com/slundberg/shap 20 comments
- GitHub - marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier https://github.com/marcotcr/lime 12 comments
- GitHub - microsoft/LightGBM: A 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. https://github.com/Microsoft/LightGBM 11 comments
- GitHub - dmlc/xgboost: Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow https://github.com/dmlc/xgboost 0 comments
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