SHAP values-Kaggle

Question 1

What do SHAP values show?

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Answer 1

• SHAP Values (an acronym from SHapley Additive exPlanations) break down a prediction to show the impact of each feature.
• Shap values show how much a given feature changed our prediction (compared to if we made that prediction at some baseline value of that feature).

A model says a bank shouldn’t loan someone money, and the bank is legally required to explain the basis for each loan rejection

Question 2

sum(SHAP values for all features) = …

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Answer 2

prediction for the instance - prediction for baseline values

Question 3

What do different types of SHAP Explainers mean e.g. DeepExplainer, KernelExplainer, TreeExplainer?

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Answer 3

shap.DeepExplainer works with Deep Learning models.
shap.KernelExplainer works with all models, though it is slower than other Explainers and it offers an approximation rather than exact Shap values.

Question 4

Calculating SHAP values can be slow. It isn’t a problem here, because this dataset is small. But you’ll want to be careful when running these to plot with reasonably sized datasets. The exception is when using an ____ model, which SHAP has some optimizations for and which is thus much faster.

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Answer 4

xgboost