update sklearn requirements

trevorstephens · Feb 15, 2020 · c03cf35 · c03cf35
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Showing 4 changed files with 6 additions and 3 deletions.
diff --git a/README.rst b/README.rst
@@ -41,5 +41,5 @@ gplearn retains the familiar scikit-learn `fit/predict` API and works with the e
 
 gplearn supports regression through the SymbolicRegressor, binary classification with the SymbolicClassifier, as well as transformation for automated feature engineering with the SymbolicTransformer, which is designed to support regression problems, but should also work for binary classification.
 
-gplearn is built on scikit-learn and a fairly recent copy (0.20.0+) is required for `installation <http://gplearn.readthedocs.io/en/stable/installation.html>`_. If you come across any issues in running or installing the package, `please submit a bug report <https://github.com/trevorstephens/gplearn/issues>`_.
+gplearn is built on scikit-learn and a fairly recent copy (0.22.1+) is required for `installation <http://gplearn.readthedocs.io/en/stable/installation.html>`_. If you come across any issues in running or installing the package, `please submit a bug report <https://github.com/trevorstephens/gplearn/issues>`_.
 
diff --git a/doc/changelog.rst b/doc/changelog.rst
@@ -9,6 +9,9 @@ Version 0.5.0
 
 - Added the `class_weight` parameter :class:`genetic.SymbolicClassifier`
   allowing users to easily compensate for imbalanced datasets.
+- Add support for Python 3.8 to ensure compatibility with ``scikit-learn``.
+  ``scikit-learn`` 0.22.1 or newer will also be required due to recent changes
+  in their testing suite.
 
 Version 0.4.1 - 1 Jun 2019
 ---------------------------

diff --git a/doc/index.rst b/doc/index.rst
@@ -65,7 +65,7 @@ for automated feature engineering with the :class:`SymbolicTransformer`, which
 is designed to support regression problems, but should also work for binary
 classification.
 
-``gplearn`` is built on scikit-learn and a fairly recent copy (0.20.0+) is required
+``gplearn`` is built on scikit-learn and a fairly recent copy (0.22.1+) is required
 for installation. If you come across any issues in running or installing the
 package, `please submit a bug report <https://github.com/trevorstephens/gplearn/issues>`_.
 

diff --git a/doc/rtd-pip-requirements b/doc/rtd-pip-requirements
@@ -1,5 +1,5 @@
 numpy>=1.8.1
 numpydoc>=0.5
 scipy>=0.13
-scikit-learn>=0.20.0
+scikit-learn>=0.22.1
 joblib>=0.13.0