WIP: Allows Silhouette Visualizer to accept DensityEstimator

tests/test_cluster/test_silhouette.py

@@ -25,6 +25,7 @@
 from sklearn.datasets import make_blobs
 from sklearn.cluster import KMeans, MiniBatchKMeans
 from sklearn.cluster import SpectralClustering, AgglomerativeClustering
+from sklearn.mixture import GaussianMixture
 
 from unittest import mock
 from tests.base import VisualTestCase
@@ -84,6 +85,29 @@ def test_integrated_mini_batch_kmeans_silhouette(self):
 
         self.assert_images_similar(visualizer, remove_legend=True)
 
+    @pytest.mark.xfail(sys.platform == "win32", reason="images not close on windows")
+    def test_integrated_gaussian_mixture_silhouette(self):
+        """
+        Test Density Estimator works with silhouette visualizer
+        """
+        # NOTE see #182: cannot use occupancy dataset because of memory usage
+
+        # Generate a blobs data set
+        X, y = make_blobs(
+            n_samples=1000, n_features=12, centers=8, shuffle=False, random_state=0
+        )
+
+        fig = plt.figure()
+        ax = fig.add_subplot()
+
+        visualizer = SilhouetteVisualizer(
+            GaussianMixture(n_components=5, random_state=0), ax=ax
+        )
+        visualizer.fit(X)
+        visualizer.finalize()
+
+        self.assert_images_similar(visualizer, remove_legend=True)
+
     @pytest.mark.skip(reason="no negative silhouette example available yet")
     def test_negative_silhouette_score(self):
         """

yellowbrick/cluster/base.py

@@ -17,7 +17,7 @@
 ## Imports
 ##########################################################################
 
-from yellowbrick.utils import isclusterer
+from yellowbrick.utils import isclusterer, isdensity
 from yellowbrick.base import ScoreVisualizer
 from yellowbrick.exceptions import YellowbrickTypeError
 
@@ -41,7 +41,7 @@ class ClusteringScoreVisualizer(ScoreVisualizer):
     """
 
     def __init__(self, estimator, ax=None, fig=None, force_model=False, **kwargs):
-        if not force_model and not isclusterer(estimator):
+        if not force_model and not isclusterer(estimator) and not isdensity(estimator):
             raise YellowbrickTypeError(
                 "The supplied model is not a clustering estimator; try a "
                 "classifier or regression score visualizer instead!"

yellowbrick/cluster/silhouette.py

@@ -188,6 +188,8 @@ def fit(self, X, y=None, **kwargs):
         # Compute the number of available clusters from the estimator
         if hasattr(self.estimator, "n_clusters"):
             self.n_clusters_ = self.estimator.n_clusters
+        elif hasattr(self.estimator, "n_components"):
+            self.n_clusters_ = self.estimator.n_components
         else:
             unique_labels = set(labels)
             n_noise_clusters = 1 if -1 in unique_labels else 0

yellowbrick/utils/types.py

@@ -116,6 +116,25 @@ def is_clusterer(estimator):
 isclusterer = is_clusterer
 
 
+def is_density(estimator):
+    """
+    Returns True if the given estimator is a Density Estimator.
+
+    Parameters
+    ----------
+    estimator : class or instance
+        The object to test if it is a Scikit-Learn clusterer, especially a
+        Scikit-Learn estimator or Yellowbrick visualizer
+    """
+
+    # Test the _estimator_type property
+    return getattr(estimator, "_estimator_type", None) == "DensityEstimator"
+
+
+# Alias for closer name to isinstance and issubclass
+isdensity = is_density
+
+
 def is_gridsearch(estimator):
     """
     Returns True if the given estimator is a clusterer.