8000 MRG Check that X is non_zero for MultinomialNB. by amueller · Pull Request #908 · scikit-learn/scikit-learn · GitHub
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MRG Check that X is non_zero for MultinomialNB. #908

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MRG Check that X is non_zero for MultinomialNB. #908

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6 changes: 6 additions & 0 deletions sklearn/naive_bayes.py
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Expand Up @@ -286,6 +286,12 @@ def _count(X, Y):
N_c is the count of all features in all samples of class c;
N_c_i is the count of feature i in all samples of class c.
"""
if issparse(X):
if np.any(X.data < 0):
raise ValueError("Input X must be non-negative.")
else:
if np.any(X < 0):
raise ValueError("Input X must be non-negative.")
N_c_i = safe_sparse_dot(Y.T, X)
N_c = np.sum(N_c_i, axis=1)

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1 change: 1 addition & 0 deletions sklearn/tests/test_naive_bayes.py
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Expand Up @@ -73,6 +73,7 @@ def test_mnnb():
for X in [X2, scipy.sparse.csr_matrix(X2)]:
# Check the ability to predict the learning set.
clf = MultinomialNB()
assert_raises(ValueError, clf.fit, -X, y2)
y_pred = clf.fit(X, y2).predict(X)

assert_array_equal(y_pred, y2)
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0