FIX avoid division by 0 warning in LabelPropagation (#15946)

ngshya · glemaitre · commit 50d3fe963c3d · 2020-01-09T19:12:25.000+01:00
diff --git a/sklearn/semi_supervised/_label_propagation.py b/sklearn/semi_supervised/_label_propagation.py
@@ -290,6 +290,7 @@ def fit(self, X, y):
             self.n_iter_ += 1
 
         normalizer = np.sum(self.label_distributions_, axis=1)[:, np.newaxis]
+        normalizer[normalizer == 0] = 1
         self.label_distributions_ /= normalizer
 
         # set the transduction item
diff --git a/sklearn/semi_supervised/tests/test_label_propagation.py b/sklearn/semi_supervised/tests/test_label_propagation.py
@@ -157,6 +157,18 @@ def test_convergence_warning():
     assert_no_warnings(mdl.fit, X, y)
 
 
+def test_label_propagation_non_zero_normalizer():
+    # check that we don't divide by zero in case of null normalizer
+    # non-regression test for
+    # https://github.com/scikit-learn/scikit-learn/pull/15946
+    X = np.array([[100., 100.], [100., 100.], [0., 0.], [0., 0.]])
+    y = np.array([0, 1, -1, -1])
+    mdl = label_propagation.LabelSpreading(kernel='knn',
+                                           max_iter=100,
+                                           n_neighbors=1)
+    assert_no_warnings(mdl.fit, X, y)
+
+
 def test_predict_sparse_callable_kernel():
     # This is a non-regression test for #15866
 
