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Commit 2f99cda

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101AlexMartinAlexMGTNOjeremiedbbglemaitre
authored
API replace mean_squared_error(square=False) by root_mean_squared_error (#26734)
Co-authored-by: Alejandro Martin <alejandro.martingil@tno.nl> Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
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‎doc/modules/classes.rst

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@@ -995,6 +995,8 @@ details.
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metrics.median_absolute_error
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metrics.mean_absolute_percentage_error
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metrics.r2_score
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metrics.root_mean_squared_log_error
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metrics.root_mean_squared_error
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metrics.mean_poisson_deviance
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metrics.mean_gamma_deviance
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metrics.mean_tweedie_deviance

‎doc/modules/model_evaluation.rst

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@@ -94,8 +94,9 @@ Scoring Function
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'max_error' :func:`metrics.max_error`
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'neg_mean_absolute_error' :func:`metrics.mean_absolute_error`
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'neg_mean_squared_error' :func:`metrics.mean_squared_error`
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'neg_root_mean_squared_error' :func:`metrics.mean_squared_error`
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'neg_root_mean_squared_error' :func:`metrics.root_mean_squared_error`
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'neg_mean_squared_log_error' :func:`metrics.mean_squared_log_error`
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'neg_root_mean_squared_log_error' :func:`metrics.root_mean_squared_log_error`
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'neg_median_absolute_error' :func:`metrics.median_absolute_error`
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'r2' :func:`metrics.r2_score`
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'neg_mean_poisson_deviance' :func:`metrics.mean_poisson_deviance`
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for an example of mean squared error usage to
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evaluate gradient boosting regression.
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Taking the square root of the MSE, called the root mean squared error (RMSE), is another
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common metric that provides a measure in the same units as the target variable. RSME is
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available through the :func:`root_mean_squared_error` function.
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.. _mean_squared_log_error:
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Mean squared logarithmic error
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>>> mean_squared_log_error(y_true, y_pred)
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0.044...
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The root mean squared logarithmic error (RMSLE) is available through the
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:func:`root_mean_squared_log_error` function.
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.. _mean_absolute_percentage_error:
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Mean absolute percentage error

‎doc/whats_new/v1.4.rst

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- |Enhancement| :class:`preprocessing.TargetEncoder` now supports `target_type`
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'multiclass'. :pr:`26674` by :user:`Lucy Liu <lucyleeow>`.
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:mod:`sklearn.metrics`
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......................
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- |API| The `squared` parameter of :func:`metrics.mean_squared_error` and
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:func:`metrics.mean_squared_log_error` is deprecated and will be removed in 1.6.
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Use the new functions :func:`metrics.root_mean_squared_error` and
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:func:`root_mean_squared_log_error` instead.
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:pr:`26734` by :user:`Alejandro Martin Gil <101AlexMartin>`.
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- |Enhancement| Added `neg_root_mean_squared_log_error_scorer` as scorer
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:pr:`26734` by :user:`Alejandro Martin Gil <101AlexMartin>`.
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:mod:`sklearn.model_selection`
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..............................
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‎sklearn/metrics/__init__.py

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mean_tweedie_deviance,
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median_absolute_error,
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r2_score,
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root_mean_squared_error,
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root_mean_squared_log_error,
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)
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from ._scorer import check_scoring, get_scorer, get_scorer_names, make_scorer
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from .cluster import (
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"RocCurveDisplay",
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"roc_auc_score",
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"roc_curve",
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"root_mean_squared_log_error",
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"root_mean_squared_error",
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"get_scorer_names",
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"silhouette_samples",
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"silhouette_score",

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