You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
What I am expecting to see is that the sum of shap values for all features be equal to target variable minus expected value of target. This is true for mean output (model_output=0). But as shown in the last cell of the linked notebook, the scale output does not satisfy this. This is most probably a question, rather than a bug or issue, but it still can be helpful for future reference to be asked here.
The text was updated successfully, but these errors were encountered:
I faced the same issue because I wanted to interpret the Shap Values for NGBoost using Gamma distribution.
Short Answer:
Shapley values are calcolated for param[0] and param[1] depending on what you select on model_output.
The problem is that params[0] and params[1] mean different things depending on the considered distribution.
For example, I opened the folder "ngboost/ngboost/distns" and check the gamma.py. You clearly notice the relation between alpha and beta and params at rows 39 and 40 (and below for convenience):
Hi and thanks for the great work ! I am having trouble understanding what the shap values for
model_output=1
represent. Here is a sample notebook:https://github.com/AliSamiiXOM/ngboost_question/blob/main/shap_with_ngboost.ipynb.
What I am expecting to see is that the sum of shap values for all features be equal to target variable minus expected value of target. This is true for mean output (model_output=0). But as shown in the last cell of the linked notebook, the scale output does not satisfy this. This is most probably a question, rather than a bug or issue, but it still can be helpful for future reference to be asked here.
The text was updated successfully, but these errors were encountered: