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Interpretable machine learning with SHAP

 Posted on January 24, 2021

In this post, we predict health insurance costs with an efficient black box model, namely random forest. Then we interpret individual predictions as well as the global behavior of the estimator using SHapley Additive exPlanations. [Read More]
interpretability  explainability  Shapley  SHAP  correlation  multicollinearity  python  black box  insurance 

Vincent Le Goualher  • © 2023  •  VLG Data Engineering

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