import sklearn.metrics
import numpy as np
# Evaluation function for regressors
[docs]def explained_variance(y_true, y_pred, **args):
"""Explained variance score based on the `sklearn.metrics.explained_variance_score`_ function.
More details here : `Explained variance score`_
.. _sklearn.metrics.explained_variance_score: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.explained_variance_score.html#sklearn.metrics.explained_variance_score
.. _Explained variance score: https://scikit-learn.org/stable/modules/model_evaluation.html#explained-variance-score
"""
return sklearn.metrics.explained_variance_score(y_true, y_pred, **args)
[docs]def max_error(y_true, y_pred, **args):
"""Max error based on the `sklearn.metrics.max_error`_ function.
More details here : `Max error`_
.. _sklearn.metrics.max_error: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.max_error.html#sklearn.metrics.max_error
.. _Max error: https://scikit-learn.org/stable/modules/model_evaluation.html#max-error
"""
return sklearn.metrics.max_error(y_true, y_pred, **args)
[docs]def mean_absolute_error(y_true, y_pred, **args):
"""Mean absolute error based on the `sklearn.metrics.mean_absolute_error`_ function.
More details here : `Mean absolute error`_
.. _sklearn.metrics.mean_absolute_error: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html#sklearn.metrics.mean_absolute_error
.. _Mean absolute error: https://scikit-learn.org/stable/modules/model_evaluation.html#mean-absolute-error
"""
return sklearn.metrics.mean_absolute_error(y_true, y_pred, **args)
[docs]def mean_squared_error(y_true, y_pred, **args):
"""Mean squared error based on the `sklearn.metrics.mean_squared_error`_ function.
More details here : `Mean squared error`_
.. _sklearn.metrics.mean_squared_error: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html#sklearn.metrics.mean_squared_error
.. _Mean squared error: https://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-error
"""
return sklearn.metrics.mean_squared_error(y_true, y_pred, **args)
[docs]def root_mean_squared_error(y_true, y_pred, **args):
"""Root mean squared error based on the `sklearn.metrics.mean_squared_error`_ function.
squared argument is set to False.
More details here : `Mean squared error`_
.. _sklearn.metrics.mean_squared_error: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html#sklearn.metrics.mean_squared_error
.. _Mean squared error: https://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-error
"""
return sklearn.metrics.mean_squared_error(y_true, y_pred, squared=False, **args)
[docs]def mean_squared_log_error(y_true, y_pred, **args):
"""Mean squared logarithmic error based on the `sklearn.metrics.mean_squared_log_error`_ function.
More details here : `Mean squared logarithmic error`_
.. _sklearn.metrics.mean_squared_log_error: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_log_error.html#sklearn.metrics.mean_squared_log_error
.. _Mean squared logarithmic error: https://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-log-error
"""
return sklearn.metrics.mean_squared_log_error(y_true, y_pred, **args)
[docs]def r2(y_true, y_pred, **args):
"""R² score, the coefficient of determination
based on the `sklearn.metrics.r2_score`_ function.
More details here : `R² score, the coefficient of determination`_
.. _sklearn.metrics.r2_score: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html#sklearn.metrics.r2_score
.. _R² score, the coefficient of determination: https://scikit-learn.org/stable/modules/model_evaluation.html#r2-score-the-coefficient-of-determination
"""
return sklearn.metrics.r2_score(y_true, y_pred, **args)
[docs]def mean_poisson_deviance(y_true, y_pred, **args):
"""Mean Poisson deviances based on the `sklearn.metrics.mean_poisson_deviance`_ function.
More details here : `Mean Poisson, Gamma, and Tweedie deviances`_
.. _sklearn.metrics.mean_poisson_deviance: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_poisson_deviance.html#sklearn.metrics.mean_poisson_deviance
.. _Mean Poisson, Gamma, and Tweedie deviances: https://scikit-learn.org/stable/modules/model_evaluation.html#mean-tweedie-deviance
"""
return sklearn.metrics.mean_poisson_deviance(y_true, y_pred, **args)
[docs]def mean_gamma_deviance(y_true, y_pred, **args):
"""Mean Gamma deviance based on the `sklearn.metrics.mean_gamma_deviance`_ function.
More details here : `Mean Poisson, Gamma, and Tweedie deviances`_
.. _sklearn.metrics.mean_gamma_deviance: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_gamma_deviance.html#sklearn.metrics.mean_gamma_deviance
.. _Mean Poisson, Gamma, and Tweedie deviances: https://scikit-learn.org/stable/modules/model_evaluation.html#mean-tweedie-deviance
"""
return sklearn.metrics.mean_gamma_deviance(y_true, y_pred, **args)