Question about apartment price example in Shapley Values chapter

[jtr13]

Based on this description it sounds like you are applying the permutation method for SHAP rather than the original method for Shapley values, which, if I understand correctly, would involve fitting new models to test predictions with and without a particular feature, rather than substituting random values for the absent features.

"Figure 17.2 shows how to calculate the marginal contribution of the cat-banned feature value when it is added to a coalition of park-nearby and area-50. We simulate that only park-nearby, cat-banned, and area-50 are in a coalition by randomly drawing another apartment from the data and using its value for the floor feature. The value floor-2nd was replaced by the randomly drawn floor-1st. Then we predict the price of the apartment with this combination (€310,000). In a second step, we remove cat-banned from the coalition by replacing it with a random value of the cat allowed/banned feature from the randomly drawn apartment. In the example, it was cat-allowed, but it could have been cat-banned again. We predict the apartment price for the coalition of park-nearby and area-50 (€320,000). The contribution of cat-banned was €310,000 - €320,000 = -€10,000. This estimate depends on the values of the randomly drawn apartment that served as a “donor” for the cat and floor feature values. We’ll get better estimates if we repeat this sampling step and average the contributions."