update release notes

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.