BUG allow array-like y in RFE

larsmans · GaelVaroquaux · commit 9a3910da1806 · 2012-10-06T15:52:41.000+02:00
+ cosmit: use np.ravel to flatten np.matrix
diff --git a/sklearn/feature_selection/rfe.py b/sklearn/feature_selection/rfe.py
@@ -149,7 +149,7 @@ def fit(self, X, y):
                 ranks = np.argsort(safe_sqr(estimator.coef_))
 
             # for sparse case ranks is matrix
-            ranks = np.asarray(ranks).ravel()
+            ranks = np.ravel(ranks)
 
             # Eliminate the worse features
             threshold = min(step, np.sum(support_) - n_features_to_select)
@@ -327,6 +327,7 @@ def fit(self, X, y):
             Target values (integers for classification, real numbers for
             regression).
         """
+        X, y = check_arrays(X, y, sparse_format="csr")
         # Initialization
         rfe = RFE(estimator=self.estimator, n_features_to_select=1,
                 step=self.step, estimator_params=self.estimator_params,
diff --git a/sklearn/feature_selection/tests/test_rfe.py b/sklearn/feature_selection/tests/test_rfe.py
@@ -64,7 +64,7 @@ def test_rfecv():
 
     iris = load_iris()
     X = np.c_[iris.data, generator.normal(size=(len(iris.data), 6))]
-    y = iris.target
+    y = list(iris.target)   # regression test: list should be supported
 
     # Test using the score function
     rfecv = RFECV(estimator=SVC(kernel="linear"), step=1, cv=3)
