Import from sklearn 0.18 new module sklearn.model_selection to avoid DeprecationWarnings

Author: dukebody

README.rst

@@ -220,7 +220,7 @@ To get around this, sklearn-pandas provides a wrapper on sklearn's ``cross_val_s
     >>> pipe = sklearn.pipeline.Pipeline([
     ...     ('featurize', mapper),
     ...     ('lm', sklearn.linear_model.LinearRegression())])
-    >>> np.round(cross_val_score(pipe, data.copy(), data.salary, 'r2'), 2)
+    >>> np.round(cross_val_score(pipe, X=data.copy(), y=data.salary, scoring='r2'), 2)
     array([ -1.09,  -5.3 , -15.38])
 
 Sklearn-pandas' ``cross_val_score`` function provides exactly the same interface as sklearn's function of the same name.

sklearn_pandas/cross_validation.py

@@ -1,6 +1,12 @@
 import warnings
-from sklearn import cross_validation
-from sklearn import grid_search
+try:
+    from sklearn.model_selection import cross_val_score as sk_cross_val_score
+    from sklearn.model_selection import GridSearchCV as SKGridSearchCV
+    from sklearn.model_selection import RandomizedSearchCV as SKRandomizedSearchCV
+except ImportError:
+    from sklearn.cross_validation import cross_val_score as sk_cross_val_score
+    from sklearn.grid_search import GridSearchCV as SKGridSearchCV
+    from sklearn.grid_search import RandomizedSearchCV as SKRandomizedSearchCV
 
 DEPRECATION_MSG = '''
     Custom cross-validation compatibility shims are no longer needed for
@@ -11,10 +17,10 @@
 def cross_val_score(model, X, *args, **kwargs):
     warnings.warn(DEPRECATION_MSG, DeprecationWarning)
     X = DataWrapper(X)
-    return cross_validation.cross_val_score(model, X, *args, **kwargs)
+    return sk_cross_val_score(model, X, *args, **kwargs)
 
 
-class GridSearchCV(grid_search.GridSearchCV):
+class GridSearchCV(SKGridSearchCV):
     def __init__(self, *args, **kwargs):
         warnings.warn(DEPRECATION_MSG, DeprecationWarning)
         super(GridSearchCV, self).__init__(*args, **kwargs)
@@ -27,7 +33,7 @@ def predict(self, X, *params, **kwparams):
 
 
 try:
-    class RandomizedSearchCV(grid_search.RandomizedSearchCV):
+    class RandomizedSearchCV(SKRandomizedSearchCV):
         def __init__(self, *args, **kwargs):
             warnings.warn(DEPRECATION_MSG, DeprecationWarning)
             super(RandomizedSearchCV, self).__init__(*args, **kwargs)