Comments (1)
There are two KDE-based samplers in eli5.lime now, so I'm closing this ticket.
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Related Issues (20)
- Explaining multi-input model HOT 1
- import show_prediction issue HOT 3
- eli5 explains the importance of features by category
- pandas.core.indexes.base.Index not supported for feature_names params in show_weights
- How weights are calculated during local explainations?
- More detailed documentation of eli5.explain_prediction?
- PermutationImportance uses CV splitter indexes incorrectly
- Error: estimator XGBClassifier is not supported
- Making the world a cleaner place
- TypeError: check_cv() takes from 0 to 2 positional arguments but 3 were given HOT 2
- explain_prediction_lightgbm doesnt work for microsoft lightgbm HOT 1
- Pin version of jinja2 (and markupsafe) in requirements
- AttributeError when importing eli5 0.11.0
- Looping with explain_prediction_df crashes
- eli5.show_prediction doesn't work for my custom trained model
- Understanding show_weights html
- Pairing RFECV and RandomForestRegressor with non-cv Permutation Importance returns NotFittedError
- Error importing eli5.lime due to deprecated 'itemfreq' from 'scipy.stats'
- Error : Estimator is not supported
- Does not support scikit-learn=1.3.0 HOT 7
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