8000 [MRG] Use _check_sample_weight in GaussianNB by MDouriez · Pull Request #15480 · scikit-learn/scikit-learn · GitHub
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[MRG] Use _check_sample_weight in GaussianNB #15480

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Merged
merged 4 commits into from
Nov 6, 2019
Merged

[MRG] Use _check_sample_weight in GaussianNB #15480

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e1d3fa1
wip
MDouriez Nov 2, 2019
d5f8e61
flake8
MDouriez Nov 2, 2019
89e92bf
remove dtype
MDouriez Nov 2, 2019
0e0d377
Merge branch 'master' into 15358_GaussianNB
rth Nov 6, 2019
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8 changes: 3 additions & 5 deletions sklearn/naive_bayes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,18 +21,17 @@


import numpy as np
from scipy.sparse import issparse

from .base import BaseEstimator, ClassifierMixin
from .preprocessing import binarize
from .preprocessing import LabelBinarizer
from .preprocessing import label_binarize
from .utils import check_X_y, check_array, check_consistent_length
from .utils import check_X_y, check_array, deprecated
from .utils.extmath import safe_sparse_dot
from .utils.fixes import logsumexp
from .utils.multiclass import _check_partial_fit_first_call
from .utils.validation import check_is_fitted, check_non_negative, column_or_1d
from .utils import deprecated
from .utils.validation import _check_sample_weight

__all__ = ['BernoulliNB', 'GaussianNB', 'MultinomialNB', 'ComplementNB',
'CategoricalNB']
Expand Down Expand Up @@ -360,8 +359,7 @@ def _partial_fit(self, X, y, classes=None, _refit=False,
"""
X, y = check_X_y(X, y)
if sample_weight is not None:
sample_weight = check_array(sample_weight, ensure_2d=False)
check_consistent_length(y, sample_weight)
sample_weight = _check_sample_weight(sample_weight, X)

# If the ratio of data variance between dimensions is too small, it
# will cause numerical errors. To address this, we artificially
Expand Down
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