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[MRG + 1] Raising an error when n_clusters <= 0 in AgglomerativeClustering #4423

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Mar 31, 2015
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[MRG + 1] Raising an error when n_clusters <= 0 in AgglomerativeClustering #4423

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4 changes: 4 additions & 0 deletions sklearn/cluster/hierarchical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -712,6 +712,10 @@ def fit(self, X, y=None):
if isinstance(memory, six.string_types):
memory = Memory(cachedir=memory, verbose=0)

if self.n_clusters <= 0:
raise ValueError("n_clusters should be an integer greater than 0."
" %s was provided." % str(self.n_clusters))

if self.linkage == "ward" and self.affinity != "euclidean":
raise ValueError("%s was provided as affinity. Ward can only "
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@amueller - I was trying to make it similar to this error message for uniformity, but I agree that the problem should be specified first. :)

"work with euclidean distances." %
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11 changes: 11 additions & 0 deletions sklearn/cluster/tests/test_hierarchical.py
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Expand Up @@ -18,6 +18,7 @@
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raise_message
from sklearn.utils.testing import ignore_warnings

from sklearn.cluster import ward_tree
Expand Down Expand Up @@ -501,6 +502,16 @@ def test_n_components():
for linkage_func in _TREE_BUILDERS.values():
assert_equal(ignore_warnings(linkage_func)(X, connectivity)[1], 5)

def test_agg_n_clusters():
# Test that an error is raised when n_clusters <= 0

rng = np.random.RandomState(0)
X = rng.rand(20, 10)
for n_clus in [-1, 0]:
agc = AgglomerativeClustering(n_clusters=n_clus)
msg = ("n_clusters should be an integer greater than 0."
" %s was provided." % str(agc.n_clusters))
assert_raise_message(ValueError, msg, agc.fit, X)

if __name__ == '__main__':
import nose
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