FIX Fixes TheilSenRegressor with fit_intercept=False and one feature (scikit-learn#18121)

thomasjpfan · web-flow · commit 06c710ade0a8 · 2020-10-09T18:29:59.000+02:00
diff --git a/doc/whats_new/v0.24.rst b/doc/whats_new/v0.24.rst
@@ -346,6 +346,9 @@ Changelog
   efficient leave-one-out cross-validation scheme ``cv=None``. :pr:`6624` by
   :user:`Marijn van Vliet <wmvanvliet>`.
 
+- |Fix| Fixes bug in :class:`linear_model.TheilSenRegressor` where
+  `predict` and `score` would fail when `fit_intercept=False` and there was
+  one feature during fitting. :pr:`18121` by `Thomas Fan`_.
 
 :mod:`sklearn.manifold`
 .......................
diff --git a/sklearn/linear_model/_theil_sen.py b/sklearn/linear_model/_theil_sen.py
@@ -110,7 +110,7 @@ def _spatial_median(X, max_iter=300, tol=1.e-3):
       http://users.jyu.fi/~samiayr/pdf/ayramo_eurogen05.pdf
     """
     if X.shape[1] == 1:
-        return 1, np.median(X.ravel())
+        return 1, np.median(X.ravel(), keepdims=True)
 
     tol **= 2  # We are computing the tol on the squared norm
     spatial_median_old = np.mean(X, axis=0)
@@ -125,7 +125,6 @@ def _spatial_median(X, max_iter=300, tol=1.e-3):
         warnings.warn("Maximum number of iterations {max_iter} reached in "
                       "spatial median for TheilSen regressor."
                       "".format(max_iter=max_iter), ConvergenceWarning)
-
     return n_iter, spatial_median
 
 
diff --git a/sklearn/linear_model/tests/test_theil_sen.py b/sklearn/linear_model/tests/test_theil_sen.py
@@ -179,6 +179,9 @@ def test_theil_sen_1d_no_intercept():
     assert_array_almost_equal(theil_sen.coef_, w + c, 1)
     assert_almost_equal(theil_sen.intercept_, 0.)
 
+    # non-regression test for #18104
+    theil_sen.score(X, y)
+
 
 def test_theil_sen_2d():
     X, y, w, c = gen_toy_problem_2d()
