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Kde doc fix #11275

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Merged
merged 2 commits into from
Sep 28, 2018
Merged

Kde doc fix #11275

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Jun 15, 2018
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Jun 15, 2018
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10 changes: 7 additions & 3 deletions sklearn/neighbors/kde.py
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Original file line number Diff line number Diff line change
Expand Up @@ -144,7 +144,9 @@ def score_samples(self, X):
Returns
-------
density : ndarray, shape (n_samples,)
The array of log(density) evaluations.
The array of log(density) evaluations. These are normalized to be
probability densities, so values will be low for high-dimensional
data.
"""
# The returned density is normalized to the number of points.
# For it to be a probability, we must scale it. For this reason
Expand All @@ -159,7 +161,7 @@ def score_samples(self, X):
return log_density

def score(self, X, y=None):
"""Compute the total log probability under the model.
"""Compute the total log probability density under the model.

Parameters
----------
Expand All @@ -170,7 +172,9 @@ def score(self, X, y=None):
Returns
-------
logprob : float
Total log-likelihood of the data in X.
Total log-likelihood of the data in X. This is normalized to be a
probability density, so the value will be low for high-dimensional
data.
"""
return np.sum(self.score_samples(X))

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