Release (#1961)

docs/source/release_notes.rst

@@ -1,13 +1,21 @@
 Release Notes
 -------------
 **Future Releases**
+    * Enhancements
+    * Fixes
+    * Changes
+    * Documentation Changes
+    * Testing Changes
+
+**v0.20.0 Mar. 10, 2021**
     * Enhancements
         * Added a GitHub Action for Detecting dependency changes :pr:`1933`
         * Create a separate CV split to train stacked ensembler on for AutoMLSearch :pr:`1814`
         * Added a GitHub Action for Linux unit tests :pr:`1846`
         * Added ``DataCheckAction`` class and ``DataCheckActionCode`` enum :pr:`1896`
         * Updated ``Woodwork`` requirement to ``v0.0.10`` :pr:`1900`
         * Added ``BalancedClassificationDataCVSplit`` and ``BalancedClassificationDataTVSplit`` to AutoMLSearch :pr:`1875`
+        * Update default classification data splitter to use downsampling for highly imbalanced data :pr:`1875`
         * Updated ``describe_pipeline`` to return more information, including ``id`` of pipelines used for ensemble models :pr:`1909`
         * Added utility method to create list of components from a list of ``DataCheckAction`` :pr:`1907`
         * Updated ``validate`` method to include a ``action`` key in returned dictionary for all ``DataCheck``and ``DataChecks`` :pr:`1916`

evalml/__init__.py

@@ -22,4 +22,4 @@
 warnings.filterwarnings('ignore', 'The following selectors were not present in your DataTable')
 
 
-__version__ = '0.19.0'
+__version__ = '0.20.0'

setup.py

@@ -5,7 +5,7 @@
 
 setup(
     name='evalml',
-    version='0.19.0',
+    version='0.20.0',
     author='Alteryx, Inc.',
     author_email='support@featurelabs.com',
     description='EvalML is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions.',