Skip to content

FIX nan bug in BaseLabelPropagation #19271

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 13 commits into from
Feb 1, 2021
Merged
7 changes: 7 additions & 0 deletions doc/whats_new/v1.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -146,6 +146,13 @@ Changelog
for non-English characters. :pr:`18959` by :user:`Zero <Zeroto521>`
and :user:`wstates <wstates>`.

:mod:`sklearn.semi_supervised`
.................................

- |Fix| Avoid NaN during label propagation in
:class:`~sklearn.semi_supervised.LabelPropagation`.
:pr:`19271` by :user:`Zhaowei Wang <ThuWangzw>`.

Code and Documentation Contributors
-----------------------------------

Expand Down
1 change: 1 addition & 0 deletions sklearn/semi_supervised/_label_propagation.py
Original file line number Diff line number Diff line change
Expand Up @@ -279,6 +279,7 @@ def fit(self, X, y):
if self._variant == 'propagation':
normalizer = np.sum(
self.label_distributions_, axis=1)[:, np.newaxis]
normalizer[normalizer == 0] = 1
self.label_distributions_ /= normalizer
self.label_distributions_ = np.where(unlabeled,
self.label_distributions_,
Expand Down
12 changes: 8 additions & 4 deletions sklearn/semi_supervised/tests/test_label_propagation.py
Original file line number Diff line number Diff line change
Expand Up @@ -157,15 +157,19 @@ def test_convergence_warning():
assert_no_warnings(mdl.fit, X, y)


def test_label_propagation_non_zero_normalizer():
@pytest.mark.parametrize("LabelPropagationCls",
[label_propagation.LabelSpreading,
label_propagation.LabelPropagation])
def test_label_propagation_non_zero_normalizer(LabelPropagationCls):
# 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
# https://github.com/scikit-learn/scikit-learn/issues/9292
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)
mdl = LabelPropagationCls(kernel='knn',
max_iter=100,
n_neighbors=1)
assert_no_warnings(mdl.fit, X, y)


Expand Down