Update minimum requirements

Change minimum requirements, so that they are compmatible with sklearn 0.23

.circleci/config.yml

@@ -11,7 +11,7 @@ jobs:
       - CONDA_ENV_NAME: testenv
       - PYTHON_VERSION: 3.6
       - NUMPY_VERSION: 1.13.3
-      - SKLEARN_VERSION: 0.19.1
+      - SKLEARN_VERSION: 0.20.4
       - SCIPY_VERSION: 0.19.1
       - MATPLOTLIB_VERSION: 2.1.1
       # on conda, this is the latest for python 3.5

.travis.yml

@@ -19,29 +19,29 @@ matrix:
     # Linux environment to test scikit-learn against numpy and scipy master
     # installed from their CI wheels in a virtualenv with the Python
     # interpreter provided by travis.
-    - name: "Python 3.5 - scikit 0.19.2"
+    - name: "Python 3.6 - scikit 0.20.4"
       python: "3.7"
       env: DISTRIB="conda" PYTHON_VERSION="3.5"
-           NUMPY_VERSION="1.12.0" SCIPY_VERSION="0.18.0" PYAML_VERSION="16.9.0"
-           SCIKIT_LEARN_VERSION="0.19.2" MATPLOTLIB_VERSION="2.0.0" COVERAGE="false"
+           NUMPY_VERSION="1.13.3" SCIPY_VERSION="0.19.1" PYAML_VERSION="16.9.0"
+           SCIKIT_LEARN_VERSION="0.20.4" MATPLOTLIB_VERSION="2.0.0" COVERAGE="false"
            JOBLIB_VERSION="0.11"
-    - name: "Python 3.6 - scikit 0.20.4"
+    - name: "Python 3.6 - scikit 0.21.3"
       python: "3.7"
       env: DISTRIB="conda" PYTHON_VERSION="3.6"
-           NUMPY_VERSION="1.14.0" SCIPY_VERSION="0.19.1" PYAML_VERSION="16.12.0"
-           SCIKIT_LEARN_VERSION="0.20.4" MATPLOTLIB_VERSION="2.0.0" COVERAGE="false"
+           NUMPY_VERSION="1.14.0" SCIPY_VERSION="1.0.0" PYAML_VERSION="16.12.0"
+           SCIKIT_LEARN_VERSION="0.21.3" MATPLOTLIB_VERSION="2.0.0" COVERAGE="false"
            JOBLIB_VERSION="0.11"
-    - name: "Python 3.7 - scikit 0.21.3"
+    - name: "Python 3.7 - scikit 0.22.1"
       python: "3.7"
       env: DISTRIB="conda" PYTHON_VERSION="3.7"
-         NUMPY_VERSION="1.16.0" SCIPY_VERSION="1.0.0" PYAML_VERSION="17.8.0"
-         SCIKIT_LEARN_VERSION="0.21.3" MATPLOTLIB_VERSION="*" COVERAGE="true"
+         NUMPY_VERSION="1.16.0" SCIPY_VERSION="1.2.0" PYAML_VERSION="17.8.0"
+         SCIKIT_LEARN_VERSION="0.22.1" MATPLOTLIB_VERSION="*" COVERAGE="true"
          JOBLIB_VERSION="0.13"
-    - name: "Python 3.8  - scikit 0.22.1"
+    - name: "Python 3.8  - scikit 0.23.0"
       python: "3.7"
       env: DISTRIB="conda" PYTHON_VERSION="3.8.1" COVERAGE="false"
            NUMPY_VERSION="1.18.1" SCIPY_VERSION="1.4.1" PYAML_VERSION="19.12.0"
-           SCIKIT_LEARN_VERSION="0.22.1" JOBLIB_VERSION="0.14.1"
+           SCIKIT_LEARN_VERSION="0.23.0" JOBLIB_VERSION="0.14.1"
     - name: "Python 3.7 - sdist check"
       python: "3.7"
       env: DISTRIB="conda" PYTHON_VERSION="3.7"

README.rst

@@ -37,6 +37,15 @@ Important links
 Install
 -------
 
+scikit-optimize requires
+
+* Python >= 3.6
+* NumPy (>= 1.13.3)
+* SciPy (>= 0.19.1)
+* joblib (>= 0.11)
+* scikit-learn >= 0.20
+* matplotlib >= 2.0.0
+
 You can install the latest release with:
 ::
 

requirements.txt

@@ -1,6 +1,6 @@
-numpy>=1.12
-scipy>=0.18
-scikit-learn>=0.19
+numpy>=1.13.3
+scipy>=0.19.1
+scikit-learn>=0.20
 matplotlib>=2.0.0
 pytest
 pyaml>=16.9

skopt/searchcv.py

@@ -14,6 +14,7 @@
 from sklearn.model_selection._search import BaseSearchCV
 from sklearn.utils import check_random_state
 from sklearn.utils.fixes import MaskedArray
+
 from sklearn.utils.validation import indexable, check_is_fitted
 try:
     from sklearn.metrics import check_scoring