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SHAP Explainer error #735
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I have got 2 questions:
1. Question:
I am trying to implement this tutorial on my own pc => https://causalml.readthedocs.io/en/latest/examples/causal_trees_interpretation.html
At TreeExplainer section here is the code that creates tree_explainer object:
I was trying to run this code on my pc but I got this error:
How can I handle it ?
2. Question:
At another implementation, I was able to get SHAP values like that:
Then I wanted to deep dive by looking locally. I have a prediction that control score ise 0.000219 and Treatment score is 0.041069. In that case I can say that I have to apply the Treatment to this data (because Treatment score is better that control score and I can see the number in the recommended_treatment column is 1). Then I plotted shap.waterfall_plot I saw that most important features for this instance always decreased the SHAP value no matter what base_value is. So I want an explenation that How should I read the SHAP plot on Uplift models cuz we know that uplift models are not as like as traditional ML models. I extremely want to know how Uplift Model decides to say "You should implement Treatment (or 2,3, whatever) to this data"
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