Comments (2)
gaugup
commented on July 27, 2024
@johnHostetter, The PR #382 has not been released as yet. Shouldn't this PR fix the issue?
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johnHostetter
commented on July 27, 2024
@johnHostetter, The PR #382 has not been released as yet. Shouldn't this PR fix the issue?
Yes, my apologies. I must have overlooked the pull request. Thank you so much for addressing this issue and for your great work in providing us with this library! I intend to use it in some upcoming research if all goes according to plan (with appropriate citations for this work, of course 😄).
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Related Issues (20)
- Support `feature_weights` param in generate_counterfactuals method
- int(final_cfs_sparse.at[cf_ix, feature]) in do_posthoc_sparsity_enhancement, do_linear_search and do_binary_search HOT 1
- CFs with onehot encoded categorical variables HOT 1
- Counterfactual Generation for only Categorical Features HOT 1
- I use tensorflow to build a regressor model, is it possible to use DiCE to interprete this model and generate CF?
- Custom probability threshold for outcome
- How to apply a timeout if counterfactual is not generated for any instance HOT 4
- Gradient Method and features_to_vary Parameter
- visualize_as_dataframe show_only_changes doesn't appear to work with floating point numbers
- VAE example not working HOT 2
- dice-ml needs to return the original classes instead of encoded classes
- How to use DICE on multi-label tasks?
- load_adult_income_dataset returns FileNotFoundError HOT 1
- visualize_as_dataframe(show_only_changes=True) does not work when categorical data is composed of numbers
- Cannot perform DataFrame operations on generated counterfactuals HOT 2
- ('Feature', ... , 'has a value outside the dataset.') caused by type mismatch HOT 3
- show(shap_local) in .py file
- TypeError: _generate_counterfactuals() got an unexpected keyword argument 'feature_weights' HOT 3
- "ValueError: DataFrame.dtypes for data must be int, float or bool. Did not expect the data types in fields" even for the columns with type as HOT 1
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