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[DOC] Remove old error functions from docstrings #21314

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Merged
merged 3 commits into from
Oct 14, 2021

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luxedo
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@luxedo luxedo commented Oct 12, 2021

What does this implement/fix? Explain your changes.

Removes "mae", "mse", "least_squares", "squared_loss", "lad", "least_absolute_deviation" and "absolute_loss" from docstrings.

Since the errors were standardized in 1.0, maybe they can be removed from the documentation, leaving only the deprecation text.

If PR #21306 is accepted, that only fixes the docstring in RandomForestRegression, It would be natural to fix the other classes documentations.

According to v1.0 changelog;

|API| The option for using the squared error via loss and criterion parameters was made more consistent. The preferred way is by setting the value to "squared_error". Old option names are still valid, produce the same models, but are deprecated and will be removed in version 1.2. :pr:19310 by :user:Christian Lorentzen <lorentzenchr>.

  • For :class:ensemble.ExtraTreesRegressor, criterion="mse" is deprecated, use "squared_error" instead which is now the default.
  • For :class:ensemble.GradientBoostingRegressor, loss="ls" is deprecated, use "squared_error" instead which is now the default.
  • For :class:ensemble.RandomForestRegressor, criterion="mse" is deprecated, use "squared_error" instead which is now the default.
  • For :class:ensemble.HistGradientBoostingRegressor, loss="least_squares" is deprecated, use "squared_error" instead which is now the default.
  • For :class:linear_model.RANSACRegressor, loss="squared_loss" is deprecated, use "squared_error" instead.
  • For :class:linear_model.SGDRegressor, loss="squared_loss" is deprecated, use "squared_error" instead which is now the default.
  • For :class:tree.DecisionTreeRegressor, criterion="mse" is deprecated, use "squared_error" instead which is now the default.
  • For :class:tree.ExtraTreeRegressor, criterion="mse" is deprecated, use "squared_error" instead which is now the default.

|API| The option for using the absolute error via loss and criterion parameters was made more consistent. The preferred way is by setting the value to "absolute_error". Old option names are still valid, produce the same models, but are deprecated and will be removed in version 1.2. :pr:19733 by :user:Christian Lorentzen <lorentzenchr>.

  • For :class:ensemble.ExtraTreesRegressor, criterion="mae" is deprecated, use "absolute_error" instead.
  • For :class:ensemble.GradientBoostingRegressor, loss="lad" is deprecated, use "absolute_error" instead.
  • For :class:ensemble.RandomForestRegressor, criterion="mae" is deprecated, use "absolute_error" instead.
  • For :class:ensemble.HistGradientBoostingRegressor, loss="least_absolute_deviation" is deprecated, use "absolute_error" instead.
  • For :class:linear_model.RANSACRegressor, loss="absolute_loss" is deprecated, use "absolute_error" instead which is now the default.
  • For :class:tree.DecisionTreeRegressor, criterion="mae" is deprecated, use "absolute_error" instead.
    For :class:tree.ExtraTreeRegressor, criterion="mae" is deprecated, use "absolute_error" instead.

So this PR also checks the following classes:

class error
ensemble.ExtraTreesRegressor "mse"
ensemble.GradientBoostingRegressor "ls"
ensemble.RandomForestRegressor "mse" #21306
ensemble.HistGradientBoostingRegressor "least_squares"
ensemble.HistGradientBoostingRegressor "least_absolute_deviation"
linear_model.RANSACRegressor "squared_loss"
linear_model.SGDRegressor "squared_loss"
tree.DecisionTreeRegressor "mse"
tree.ExtraTreeRegressor "mse"
ensemble.ExtraTreesRegressor "mae"
ensemble.GradientBoostingRegressor "lad"
ensemble.RandomForestRegressor "mae"
ensemble.HistGradientBoostingRegressor "least_absolute_deviation"
linear_model.RANSACRegressor "absolute_loss"
tree.DecisionTreeRegressor "mae"
tree.ExtraTreeRegressor "mae"

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It's indeed much clearer which ones should be used this way. Thanks!

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