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- Consider counterfactual where all PCPs see all the outcomes of specialists and not just a single PCP (public vs private full information)
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I have preprocessed a data set with one-hot encoding for all categorical features. The data has now more than 30 binary (hot encoded) (0,1) features. If I try to run the "genetic", I get the error sho…
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In chapter 1 you mention counterfactuals as equivalent to 0 the initial object.
But they have a lot more structure than 0.
An example taken from the 1973 book
[Counterfactuals](https://www.wiley.c…
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Original:
2. **Exchangeability**: We assume that within levels of relevant variables (confounders), exposed and unexposed subjects have an equal likelihood of experiencing any outcome prior to expos…
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I'm getting an error when I run [this example](https://mlr3book.mlr-org.com/chapters/chapter12/model_interpretation.html#what-if-method) from the mlr3 book:
````
Error in whatif$find_counterfactua…
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I am working on a multi-label classification task. Most of the feature values are zero. The dataset is a binary vector. When I tried to generate the counterfactual, I got the error like sparse array …
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Hi @SimonTreu ,
i just add my notes and things we discussed here as an issue, so we have everything in one place. Feel free to edit this comment with your bullet points and tasks.
- [ ] Maybe l…
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I've noticed that the counterfactuals dataframes I get from my CounterfactualExamples objects have the target value rounded to the nearest decimal place. This makes the results useless to me, since in…
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When running the below _code_ in DICE_with_advanced_option.ipynb, it dumps due to the the below error:
code:
# generate counterfactuals
dice_exp = exp.generate_counterfactuals(query_instance, tota…
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Hi,
I am trying to generate counterfactuals for a classification model. Trained the model using RandomForestClassifier.
I am expecting the target variable should show the predicted probability. I…