Explainerdashboard

Latest version: v0.4.7

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2.1

Breaking Changes
- Removed ExplainerHeader from ExplainerComponents
- so also removed parameter `header_mode` from ExplainerComponent parameters
- You can now instead syncronize pos labels across components with a PosLabelSelector
and PosLabelConnector.
- In regression plots instead of boolean ratio=True/False,
you now pass residuals={'difference', 'ratio', 'log-ratio'}
- decisiontree_df_summary renamed to decisiontree_summary_df (in line with contrib_summary_df)

New Features
- added check all shap values >-1 and <1 for model_output=probability
- added parameter pos_label to all components and ExplainerDashboard to set
the initial pos label
- added parameter block_selector_callbacks to ExplainerDashboard to block
the global pos label selector's callbacks. If you already have PosLabelSelectors
in your layout, this prevents clashes.
- plot actual vs predicted now supported only logging x axis or only y axis
- residuals plots now support option residuals='log-ratio'
- residuals-vs-col plot now shows violin plot for categorical features
- added sorting option to contributions plot/graph: sort={'abs', 'high-to-low', 'low-to-high'}
- added final prediction to contributions plot

Bug Fixes
- Interaction connector bug fixed in detailed summary: click didn't work
- pos label was ignored in explainer.plot_pdp()
- Fixed some UX issues with interations components

Improvements
- All `State['tabs', 'value']` condition have been taken out of callbacks. This
used to fix some bugs with dash tabs, but seems it works even without, so
also no need to insert dummy_tabs in `ExplainerHeader`.
- All `ExplainerComponents` now have their own pos label selector, meaning
that they are now fully self-containted and independent. No global dash
elements in component callbacks.
- You can define the layout of ExplainerComponents in a layout() method instead
of _layout(). Should still define _register_callbacks() to define callbacks
so that all subcomponents that have been registered will automatically
get their callbacks registered as well.
- Added regression `self.units` to prediction summary, shap plots,
contributions plots/table, pdp plot and trees plot.
- Clearer title for MEAN_ABS_SHAP importance and summary plots
- replace na_fill value in contributions table by "MISSING"
- add string idxs to shap and interactions summary and dependence plots,
including the violing plots
- pdp plot for classification now showing percentages instead of fractions



Other Changes
- added hide_title parameter to all components with a title
- DecisionPathGraphComponent not available for RandomForestRegression models for now.
- In contributions graph base value now called 'population average' and colored yellow.

0.4.7

Bug Fixes
- fix merge_categorical_columns when there are no cats
- Handle pandas option setting context in case it doesn't exist
- Remove is_categorical_dtype as it is getting deprecated

0.4.6.1

0.4.6

Bug Fixes
- should now work with the format of shap 0.45 that returns a three dimensional np.array instead of a list of 2-dimensional np.arrays for classifiers
-

Improvements
- Fixed several pandas warning about to be deprecated behaviours
-

0.4.5

- it seems numba and numpy are getting along better again

0.4.4

Bug Fixes
- Add warning to set `shap_kwargs=dict(check_additivity=True)` for skorch models, and switch this on for the tests.
-

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