Explainable AI Recipes by Unknown

Author:Unknown
Language: eng
Format: epub

Chapter 3 explainability for nonlinear SuperviSed ModelS

Figure 3-6. Dummy variable Location_Kolkata versus SHAP value If the location is Kolkata, then the price is expected to be lower. The reason for the difference between the two locations is the data that is being used to train the model. The previous three figures show the global importance of a feature versus the prediction function. As an example, only two features are taken into consideration. We can use all features one by one and display many graphs to understand the predictions more.

Recipe 3-6. SHAP Feature Importance

for Tree Regression Models with All Mixed

Input Variables

Problem

You want to get the global feature importance from SHAP values using mixed input feature data.

90

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