Comments (2)
I had the same error while installing the package via conda (https://anaconda.org/conda-forge/explainerdashboard). It seems to be the case that the conda version is not the latest. Either you can downgrade your dtreeviz package or update your explainerdashboard version.
At least for me, it worked after updating the package to the latest version (0.4.3).
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So the conda-forge version was behind for a while because the CI could not deal with the numpy<1.25 requirement (that was needed due to numba and the latest numpy not playing nice together). It seems it works again with the latest numpy, so I removed the requirement and now the conda-forge build works as well, so now both PyPI and conda-forge are on 0.4.5 which should be compatible with the latest version of dtreeviz...
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Related Issues (20)
- Add support for string labels
- support for pandas 2.0 HOT 2
- whatif component customization limiting range and rounding off decimal value
- Add support for CalibratedClassifierCV algorithm
- Support for GPUTree HOT 5
- ValueError: Must pass 2-d input. HOT 1
- Showcase in a HuggingFace space? HOT 1
- Dashboard is not running correctly when I am trying to use saved joblib file. HOT 3
- Dashboards not loading from saved yaml, joblib files. HOT 2
- Speed up Dashboard joblib/yaml export HOT 3
- skorch models raising The SHAP explanations do not sum up to the model's output
- integration tests failing due dash_duo.get_logs() returning None HOT 1
- Update component plots when selecting data HOT 3
- Aggregated SHAP values for one hot encoded features are overestimated
- Logodds: difference between contributions plot and prediction box
- Unexplained running out of RAM memory with ensemble voting classifier model
- shap_values should be 2d, instead shape=(200, 21, 2)! HOT 11
- [Bug] Version `0.4.6` seems to have introduced a bug - cannot access `explainer.X_merged` when `cats` not defined HOT 3
- Error when using: db = ExplainerDashboard.from_config("dashboard.yaml").flask_server() HOT 2
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