def test_integrated_mini_batch_kmeans_silhouette(self):
"""
Test no exceptions for mini-batch kmeans 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)
try:
fig = plt.figure()
ax = fig.add_subplot()
visualizer = SilhouetteVisualizer(MiniBatchKMeans(random_state=0),
ax=ax)
visualizer.fit(X)
visualizer.poof()
self.assert_images_similar(visualizer)
except Exception as e:
self.fail("error during silhouette: {}".format(e))
def test_integrated_mini_batch_kmeans_silhouette(self):
"""
Test no exceptions for mini-batch kmeans silhouette visualizer
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=True,
)
try:
visualizer = SilhouetteVisualizer(MiniBatchKMeans())
visualizer.fit(X)
visualizer.poof()
except Exception as e:
self.fail("error during silhouette: {}".format(e))
def test_integrated_mini_batch_kmeans_silhouette(self):
"""
Test no exceptions for mini-batch kmeans 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
)
try:
fig = plt.figure()
ax = fig.add_subplot()
visualizer = SilhouetteVisualizer(MiniBatchKMeans(random_state=0), ax=ax)
visualizer.fit(X)
visualizer.poof()
self.assert_images_similar(visualizer)
except Exception as e:
self.fail("error during silhouette: {}".format(e))
