From 9b3dfd0eb2691b5ab432817efb7c2f34cb19a5d6 Mon Sep 17 00:00:00 2001 From: Oege Dijk Date: Wed, 15 Jun 2022 14:11:28 +0200 Subject: [PATCH] update release notes --- RELEASE_NOTES.md | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) diff --git a/RELEASE_NOTES.md b/RELEASE_NOTES.md index 3ed18ff..5809400 100644 --- a/RELEASE_NOTES.md +++ b/RELEASE_NOTES.md @@ -1,16 +1,19 @@ # Release Notes -## Version 0.4: upgrade bootstrap5 and pipeline support -### Breaking Changes -- -- +## Version 0.4.0: upgrade bootstrap5, drop python 3.6 and 3.7 support and improved pipeline support +- Upgrades the dashboard to `bootstrap5` and `dash-bootstrap-components` `v1` (which is also based on bootstrap5), this + may break older custom dashboards that included bootstrap5 components from `dash-bootstrap-components<1` +- Support terminated for python `3.6` and `3.7` as the latest version of `scikit-learn` (1.1) dropped support as well + and explainerdashboard depends on the improved pipeline feature naming in `scikit-learn>=1.1` ### New Features -- Upgrades the dashboard to bootstrap5 and dash-bootstrap-components v1 (which is also based on bootstrap5) -- Both sklearn and imblearn Pipelines are now supported, as long as the transformers have a `.get_feature_names_out()` method +- Better support for large datasets through dynamic server-side index dropdown option selection. This means that not all indexes have to be stored client side in the browser, but + get rather automatically updated as you start typing. This should help especially with large datasets with large number of indexes. + This new server-side dynamic index dropdowns get activated if the number of rows > `max_idxs_in_dropdown` (defaults to 1000). +- Both sklearn and imblearn Pipelines are now supported with automated feature names generated, as long as all the transformers have a `.get_feature_names_out()` method - Adds `shap_kwargs` parameter to the explainers that allow you to pass additional kwargs to the shap values generating call, e.g. `shap_kwargs=dict(check_addivity=False)` -- Can now specify absolute path for `explainerfile` when dumping `dashboard.yaml` +- Can now specify absolute path with `explainerfile_absolute_path` when dumping `dashboard.yaml` with `db.to_yaml(...)` ### Bug Fixes - Suppresses warnings when extracting final model from pipeline that was not fitted on a dataframe.