Added copy argument

vighneshbirodkar · vighneshbirodkar · commit 7319923c9f44 · 2016-05-02T16:49:41.000-04:00
diff --git a/sklearn/preprocessing/data.py b/sklearn/preprocessing/data.py
@@ -1723,6 +1723,9 @@ class OneHotEncoder(BaseEstimator, TransformerMixin):
         Whether to raise an error or ignore if a unknown categorical feature is
         present during transform.
 
+    copy : bool, default=True
+        If unset, `X` maybe modified in space.
+
     Attributes
     ----------
     label_encoders_ : list of size n_features.
@@ -1757,13 +1760,14 @@ class OneHotEncoder(BaseEstimator, TransformerMixin):
 
     def __init__(self, values='auto', categorical_features="all",
                  n_values=None, dtype=np.float64, sparse=True,
-                 handle_unknown='error'):
+                 handle_unknown='error', copy=True):
         self.values = values
         self.categorical_features = categorical_features
         self.dtype = dtype
         self.sparse = sparse
         self.handle_unknown = handle_unknown
         self.n_values = n_values
+        self.copy = copy
 
     def fit(self, X, y=None):
         """Fit the CategoricalEncoder to X.
@@ -1778,7 +1782,7 @@ def fit(self, X, y=None):
         self
         """
 
-        X = check_array(X, dtype=np.object, accept_sparse='csc')
+        X = check_array(X, dtype=np.object, accept_sparse='csc', copy=self.copy)
         n_samples, n_features = X.shape
 
         _apply_selected(X, self._fit, dtype=self.dtype,
