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Merged
ogrisel merged 22 commits into from
Jun 25, 2021
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RMSLE (root mean squared log error) #20326

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Update sklearn/metrics/_regression.py
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4 changes: 4 additions & 0 deletions doc/whats_new/v1.0.rst
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Expand Up @@ -427,6 +427,10 @@ Changelog
quantile regression. :pr:`19415` by :user:`Xavier Dupré <sdpython>`
and :user:`Oliver Grisel <ogrisel>`.

- |Feature| :func:`metrics.mean_squared_log_error` now supports
`squared=False`.
:pr:`20326` by :user:`Uttam kumar <helper-uttam>`.

- |Efficiency| Improved speed of :func:`metrics.confusion_matrix` when labels
are integral.
:pr:`9843` by :user:`Jon Crall <Erotemic>`.
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9 changes: 8 additions & 1 deletion sklearn/metrics/_regression.py
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Expand Up @@ -21,6 +21,7 @@
# Konstantin Shmelkov <[email protected]>
# Christian Lorentzen <[email protected]>
# Ashutosh Hathidara <[email protected]>
# Uttam kumar <[email protected]>
# License: BSD 3 clause

import numpy as np
Expand Down Expand Up @@ -437,7 +438,7 @@ def mean_squared_error(


def mean_squared_log_error(
y_true, y_pred, *, sample_weight=None, multioutput="uniform_average"
y_true, y_pred, *, sample_weight=None, multioutput="uniform_average", squared=True
):
"""Mean squared logarithmic error regression loss.
Expand Down Expand Up @@ -466,6 +467,9 @@ def mean_squared_log_error(
'uniform_average' :
Errors of all outputs are averaged with uniform weight.
squared : bool, default=True
If True returns MSLE (mean squared log error) value.
If False returns RMSLE (root mean squared log error) value.
Returns
-------
Expand All @@ -480,6 +484,8 @@ def mean_squared_log_error(
>>> y_pred = [2.5, 5, 4, 8]
>>> mean_squared_log_error(y_true, y_pred)
0.039...
>>> mean_squared_log_error(y_true, y_pred, squared=False)
0.199...
>>> y_true = [[0.5, 1], [1, 2], [7, 6]]
>>> y_pred = [[0.5, 2], [1, 2.5], [8, 8]]
>>> mean_squared_log_error(y_true, y_pred)
Expand All @@ -505,6 +511,7 @@ def mean_squared_log_error(
np.log1p(y_pred),
sample_weight=sample_weight,
multioutput=multioutput,
squared=squared,
)


Expand Down