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Exercise

Finding key medical charge predictors with SHAP

SHAP values provide insightful explanations for predictions made by machine learning models. Now, you'll utilize SHAP to decipher the influence of various features in a RandomForestRegressor model on predicting insurance charges.

X with the predictor features and y with the insurance charges, along with the RandomForest regressor model, have been pre-loaded for you.

Please note that the code might take some time to run.

Instructions

100 XP
  • Initialize a SHAP tree explainer named explainer for the RandomForest model.
  • Calculate shap_values for the dataset.
  • Compute the mean absolute SHAP values to identify the most influential features.