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Tag: shap

SHAP Linear model waterfall with KernelExplainer and LinearExplainer

I am working on binary classification and trying to explain my model using SHAP framework. I am using logistic regression algorithm. I would like to explain this model using both KernelExplainer and LinearExplainer. So, I tried the below code from SO here This threw an error as shown below AssertionError: Unknown type passed as data object: <class ‘shap.maskers._tabular.Independent’> How can

SHAP import local_accuracy

I’m trying to test metrics from the shap library https://github.com/slundberg/shap/blob/master/shap/benchmark/metrics.py I tried calling metrics like this : But am always getting the error : Answer Try instead: Why? Inspecting package’s top level __init__.py you’ll find out the following commented line:

In Leave One Out Cross Validation, How can I Use `shap.Explainer()` Function to Explain a Machine Learning Model?

Background of the Problem I want to explain the outcome of machine learning (ML) models using SHapley Additive exPlanations (SHAP) which is implemented in the shap library of Python. As a parameter of the function shap.Explainer(), I need to pass an ML model (e.g. XGBRegressor()). However, in each iteration of the Leave One Out Cross Validation (LOOCV), the ML model

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