[MRG+1] Reorder EllipticEnvelope docstring. (scikit-learn#7734)

tguillemot · TomDLT · commit 5c60f1f4e8f6 · 2016-10-24T15:47:05.000+02:00
* Reorder EllipticEnvelope docstring.

* Fix pep8
diff --git a/sklearn/covariance/outlier_detection.py b/sklearn/covariance/outlier_detection.py
@@ -106,22 +106,6 @@ class EllipticEnvelope(ClassifierMixin, OutlierDetectionMixin, MinCovDet):
 
     Read more in the :ref:`User Guide <outlier_detection>`.
 
-    Attributes
-    ----------
-    location_ : array-like, shape (n_features,)
-        Estimated robust location
-
-    covariance_ : array-like, shape (n_features, n_features)
-        Estimated robust covariance matrix
-
-    precision_ : array-like, shape (n_features, n_features)
-        Estimated pseudo inverse matrix.
-        (stored only if store_precision is True)
-
-    support_ : array-like, shape (n_samples,)
-        A mask of the observations that have been used to compute the
-        robust estimates of location and shape.
-
     Parameters
     ----------
     store_precision : bool
@@ -146,6 +130,22 @@ class EllipticEnvelope(ClassifierMixin, OutlierDetectionMixin, MinCovDet):
         The amount of contamination of the data set, i.e. the proportion
         of outliers in the data set.
 
+    Attributes
+    ----------
+    location_ : array-like, shape (n_features,)
+        Estimated robust location
+
+    covariance_ : array-like, shape (n_features, n_features)
+        Estimated robust covariance matrix
+
+    precision_ : array-like, shape (n_features, n_features)
+        Estimated pseudo inverse matrix.
+        (stored only if store_precision is True)
+
+    support_ : array-like, shape (n_samples,)
+        A mask of the observations that have been used to compute the
+        robust estimates of location and shape.
+
     See Also
     --------
     EmpiricalCovariance, MinCovDet
