Merge pull request #4249 from ajdapretnar/clustering-test

Updated tests to sklearn=0.22.0

Author: janezd

Orange/evaluation/clustering.py

@@ -35,22 +35,18 @@ class ClusteringScore(Score):
     # pylint: disable=arguments-differ
     def from_predicted(self, results, score_function):
         # Clustering scores from labels
-        # This warning filter can be removed in scikit 0.22
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore", "The behavior of AMI will change in version 0\\.22.*")
-            if self.considers_actual:
-                return np.fromiter(
-                    (score_function(results.actual.flatten(),
-                                    predicted.flatten())
-                     for predicted in results.predicted),
-                    dtype=np.float64, count=len(results.predicted))
-            # Clustering scores from data only
-            else:
-                return np.fromiter(
-                    (score_function(results.data.X, predicted.flatten())
-                     for predicted in results.predicted),
-                    dtype=np.float64, count=len(results.predicted))
+        if self.considers_actual:
+            return np.fromiter(
+                (score_function(results.actual.flatten(),
+                                predicted.flatten())
+                 for predicted in results.predicted),
+                dtype=np.float64, count=len(results.predicted))
+        # Clustering scores from data only
+        else:
+            return np.fromiter(
+                (score_function(results.data.X, predicted.flatten())
+                 for predicted in results.predicted),
+                dtype=np.float64, count=len(results.predicted))
 
 
 class Silhouette(ClusteringScore):

Orange/tests/test_evaluation_clustering.py

@@ -35,7 +35,7 @@ def test_kmeans(self):
                                                         KMeans(n_clusters=5)])
         expected = [0.68081362, 0.55259194, 0.48851755]
         np.testing.assert_almost_equal(Silhouette(cr), expected, decimal=2)
-        expected = [0.51936073, 0.74837231, 0.59178896]
+        expected = [0.65383807, 0.75511917, 0.68721092]
         np.testing.assert_almost_equal(AdjustedMutualInfoScore(cr),
                                        expected, decimal=2)
         self.assertIsNone(cr.models)

Orange/widgets/data/tests/test_owcorrelations.py

@@ -357,7 +357,7 @@ def test_n_clusters(self):
 
     def test_get_clusters_of_attributes(self):
         clusters = self.heuristic.get_clusters_of_attributes()
-        self.assertListEqual([[0], [1, 2, 3, 4, 5, 6, 7], [8]],
+        self.assertListEqual([[1, 2, 3, 4, 5, 6, 7], [8], [0]],
                              [c.instances for c in clusters])
 
     def test_get_states(self):

requirements-core.txt

@@ -1,7 +1,7 @@
 pip>=9.0
 numpy>=1.16.0
 scipy>=0.16.1
-scikit-learn>=0.20.0
+scikit-learn>=0.22.0
 bottleneck>=1.0.0
 # Reading Excel files
 xlrd>=0.9.2