Comments (9)
that's weird. it appears there's a leaf with no observations. how many labels are in your target?
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2 labels : it is binary classification
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any chance I could get a small dataset that exhibits this behavior?
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In my first message, I provided the exact dataset (data.txt) that I'm using and which leads to the error. It contains only 57 rows and 17 columns
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oh sorry. read on my phone earlier. thanks!
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[deleted] i computed features wrong. still investigating...reproduced.
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Please pip install -U dtreeviz
. Should work now. thanks!
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@AlexandraBomane can you confirm it works?
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Hi @parrt, it works perfectly !
Many thanks for fixing the problem so quickly.
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Related Issues (20)
- from dtreeviz.trees import * Import necessary libraries HOT 1
- Color keyword argument - Value error HOT 14
- Add support for TensorFlow GradientBoostedTreesModel model
- _regr_leaf_viz calculates the mean for prediction value.
- WARNING:matplotlib.font_manager:findfont: Font family 'Arial' not found. HOT 2
- Decision Tree visualize wrong path HOT 1
- When using dataset that is different from the training for trees models - does not draw HOT 1
- Support for RandomForest HOT 5
- Visualize custom decision tree HOT 1
- how to use dtreeviz in streamlit HOT 2
- VisualisationNotYetSupportedError: get_min_samples_leaf() is not implemented yet for XGBoost. HOT 4
- TypeError: list indices must be integers or slices, not numpy.float64 HOT 5
- Crash when leaf nodes have no samples HOT 1
- Out of memory when calling viz.view() HOT 2
- Integrate AI explanation
- CatBoost need to be supported. HOT 1
- AttributeError: module 'dtreeviz' has no attribute 'model' on Windows platform, works fine on Google colab
- tfdf.keras.CartModel support? HOT 1
- TypeError: 'int' object is not subscriptable HOT 3
- Development requirement in `setup.py` HOT 1
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