Deprecate residues_ in LinearRegression

MaryanMorel · amueller · commit 76e027362fc8 · 2015-10-21T11:58:13.000+02:00
Residues can be empty if the rank of X does not satisfy the
conditions described in scipy.linalg.lstsq documentation.
As residues are not that useful (i.e. we're not doing
stat testing), this property is deprecated and will be
removed in sklearn 0.19.
diff --git a/sklearn/linear_model/base.py b/sklearn/linear_model/base.py
@@ -9,6 +9,7 @@
 #         Peter Prettenhofer <peter.prettenhofer@gmail.com>
 #         Mathieu Blondel <mathieu@mblondel.org>
 #         Lars Buitinck <L.J.Buitinck@uva.nl>
+#         Maryan Morel <maryan.morel@polytechnique.edu>
 #
 # License: BSD 3 clause
 
@@ -392,6 +393,12 @@ def __init__(self, fit_intercept=True, normalize=False, copy_X=True,
         self.copy_X = copy_X
         self.n_jobs = n_jobs
 
+    @property
+    @deprecated("residues_ is deprecated and will be removed in 0.19")
+    def residues_(self):
+        """Get the residues of the fitted model."""
+        return self._residues
+
     def fit(self, X, y, sample_weight=None):
         """
         Fit linear model.
@@ -431,16 +438,16 @@ def fit(self, X, y, sample_weight=None):
             if y.ndim < 2:
                 out = sparse_lsqr(X, y)
                 self.coef_ = out[0]
-                self.residues_ = out[3]
+                self._residues = out[3]
             else:
                 # sparse_lstsq cannot handle y with shape (M, K)
                 outs = Parallel(n_jobs=n_jobs_)(
                     delayed(sparse_lsqr)(X, y[:, j].ravel())
                     for j in range(y.shape[1]))
                 self.coef_ = np.vstack(out[0] for out in outs)
-                self.residues_ = np.vstack(out[3] for out in outs)
+                self._residues = np.vstack(out[3] for out in outs)
         else:
-            self.coef_, self.residues_, self.rank_, self.singular_ = \
+            self.coef_, self._residues, self.rank_, self.singular_ = \
                 linalg.lstsq(X, y)
             self.coef_ = self.coef_.T
 
