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Merged
merged 10 commits into from
Jun 28, 2022
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Merged

MAINT validate parameter in GaussianNB #23583

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79a58ea
Gaussian NB uses validate_params
Jitensid Jun 10, 2022
c5994d3
updated constraint for var_smoothing and docstring for priors param
Jitensid Jun 10, 2022
c35bade
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 14, 2022
aa752c5
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 14, 2022
99b7190
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 15, 2022
b653b61
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 15, 2022
e43cc87
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 16, 2022
57ced82
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 21, 2022
efc50be
Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 24, 2022
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Merge branch 'main' into gaussianNB_validate_params
Jitensid Jun 24, 2022
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14 changes: 11 additions & 3 deletions sklearn/naive_bayes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@
import warnings

from abc import ABCMeta, abstractmethod

from numbers import Real

import numpy as np
from scipy.special import logsumexp
Expand All @@ -30,7 +30,7 @@
from .utils.multiclass import _check_partial_fit_first_call
from .utils.validation import check_is_fitted, check_non_negative
from .utils.validation import _check_sample_weight

from .utils._param_validation import Interval

__all__ = [
"BernoulliNB",
Expand Down Expand Up @@ -137,7 +137,7 @@ class GaussianNB(_BaseNB):

Parameters
----------
priors : array-like of shape (n_classes,)
priors : array-like of shape (n_classes,), default=None
Prior probabilities of the classes. If specified, the priors are not
adjusted according to the data.

Expand Down Expand Up @@ -212,6 +212,11 @@ class labels known to the classifier.
[1]
"""

_parameter_constraints = {
"priors": ["array-like", None],
"var_smoothing": [Interval(Real, 0, None, closed="left")],
}

def __init__(self, *, priors=None, var_smoothing=1e-9):
self.priors = priors
self.var_smoothing = var_smoothing
Expand Down Expand Up @@ -239,6 +244,7 @@ def fit(self, X, y, sample_weight=None):
self : object
Returns the instance itself.
"""
self._validate_params()
y = self._validate_data(y=y)
return self._partial_fit(
X, y, np.unique(y), _refit=True, sample_weight=sample_weight
Expand Down Expand Up @@ -360,6 +366,8 @@ def partial_fit(self, X, y, classes=None, sample_weight=None):
self : object
Returns the instance itself.
"""
self._validate_params()

return self._partial_fit(
X, y, classes, _refit=False, sample_weight=sample_weight
)
Expand Down
1 change: 0 additions & 1 deletion sklearn/tests/test_common.py
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Expand Up @@ -483,7 +483,6 @@ def test_estimators_do_not_raise_errors_in_init_or_set_params(Estimator):
"FunctionTransformer",
"GammaRegressor",
"GaussianMixture",
"GaussianNB",
"GaussianProcessClassifier",
"GaussianProcessRegressor",
"GaussianRandomProjection",
Expand Down