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Commit 8a5d8c3

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OmarManzoorOmarManzoor
authored
FEA Add metadata routing for TransformedTargetRegressor (#29136)
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‎doc/metadata_routing.rst

Copy file name to clipboardExpand all lines: doc/metadata_routing.rst
+1-1Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -276,6 +276,7 @@ Meta-estimators and functions supporting metadata routing:
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- :class:`sklearn.calibration.CalibratedClassifierCV`
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- :class:`sklearn.compose.ColumnTransformer`
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- :class:`sklearn.compose.TransformedTargetRegressor`
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- :class:`sklearn.covariance.GraphicalLassoCV`
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- :class:`sklearn.ensemble.StackingClassifier`
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- :class:`sklearn.ensemble.StackingRegressor`
@@ -316,7 +317,6 @@ Meta-estimators and functions supporting metadata routing:
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Meta-estimators and tools not supporting metadata routing yet:
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319-
- :class:`sklearn.compose.TransformedTargetRegressor`
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- :class:`sklearn.ensemble.AdaBoostClassifier`
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- :class:`sklearn.ensemble.AdaBoostRegressor`
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- :class:`sklearn.feature_selection.RFE`

‎doc/whats_new/v1.6.rst

Copy file name to clipboardExpand all lines: doc/whats_new/v1.6.rst
+5Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -67,6 +67,11 @@ more details.
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``**fit_params`` to the underlying estimators via their `fit` methods.
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:pr:`28701` by :user:`Stefanie Senger <StefanieSenger>`.
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- |Feature| :class:`compose.TransformedTargetRegressor` now supports metadata
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routing in its `fit` and `predict` methods and routes the corresponding
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params to the underlying regressor.
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:pr:`29136` by :user:`Omar Salman <OmarManzoor>`.
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7075
Dropping official support for PyPy
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----------------------------------
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‎sklearn/compose/_target.py

Copy file name to clipboardExpand all lines: sklearn/compose/_target.py
+74-19Lines changed: 74 additions & 19 deletions
Original file line numberDiff line numberDiff line change
@@ -8,12 +8,18 @@
88

99
from ..base import BaseEstimator, RegressorMixin, _fit_context, clone
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from ..exceptions import NotFittedError
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from ..linear_model import LinearRegression
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from ..preprocessing import FunctionTransformer
12-
from ..utils import _safe_indexing, check_array
13+
from ..utils import Bunch, _safe_indexing, check_array
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from ..utils._metadata_requests import (
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MetadataRouter,
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MethodMapping,
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_routing_enabled,
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process_routing,
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)
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from ..utils._param_validation import HasMethods
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from ..utils._tags import _safe_tags
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from ..utils.metadata_routing import (
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_raise_for_unsupported_routing,
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_RoutingNotSupportedMixin,
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)
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from ..utils.validation import check_is_fitted
@@ -230,15 +236,25 @@ def fit(self, X, y, **fit_params):
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Target values.
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**fit_params : dict
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Parameters passed to the `fit` method of the underlying
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regressor.
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- If `enable_metadata_routing=False` (default):
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Parameters directly passed to the `fit` method of the
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underlying regressor.
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- If `enable_metadata_routing=True`:
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Parameters safely routed to the `fit` method of the
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underlying regressor.
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.. versionchanged:: 1.6
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See :ref:`Metadata Routing User Guide <metadata_routing>` for
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more details.
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Returns
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-------
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self : object
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Fitted estimator.
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"""
241-
_raise_for_unsupported_routing(self, "fit", **fit_params)
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if y is None:
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raise ValueError(
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f"This {self.__class__.__name__} estimator "
@@ -274,14 +290,13 @@ def fit(self, X, y, **fit_params):
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if y_trans.ndim == 2 and y_trans.shape[1] == 1:
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y_trans = y_trans.squeeze(axis=1)
276292

277-
if self.regressor is None:
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from ..linear_model import LinearRegression
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self.regressor_ = LinearRegression()
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self.regressor_ = self._get_regressor(get_clone=True)
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if _routing_enabled():
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routed_params = process_routing(self, "fit", **fit_params)
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else:
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self.regressor_ = clone(self.regressor)
297+
routed_params = Bunch(regressor=Bunch(fit=fit_params))
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284-
self.regressor_.fit(X, y_trans, **fit_params)
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self.regressor_.fit(X, y_trans, **routed_params.regressor.fit)
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if hasattr(self.regressor_, "feature_names_in_"):
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self.feature_names_in_ = self.regressor_.feature_names_in_
@@ -300,16 +315,32 @@ def predict(self, X, **predict_params):
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Samples.
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**predict_params : dict of str -> object
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Parameters passed to the `predict` method of the underlying
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regressor.
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- If `enable_metadata_routing=False` (default):
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320+
Parameters directly passed to the `predict` method of the
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underlying regressor.
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- If `enable_metadata_routing=True`:
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325+
Parameters safely routed to the `predict` method of the
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underlying regressor.
327+
328+
.. versionchanged:: 1.6
329+
See :ref:`Metadata Routing User Guide <metadata_routing>`
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for more details.
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Returns
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-------
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y_hat : ndarray of shape (n_samples,)
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Predicted values.
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"""
311337
check_is_fitted(self)
312-
pred = self.regressor_.predict(X, **predict_params)
338+
if _routing_enabled():
339+
routed_params = process_routing(self, "predict", **predict_params)
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else:
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routed_params = Bunch(regressor=Bunch(predict=predict_params))
342+
343+
pred = self.regressor_.predict(X, **routed_params.regressor.predict)
313344
if pred.ndim == 1:
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pred_trans = self.transformer_.inverse_transform(pred.reshape(-1, 1))
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else:
@@ -324,11 +355,7 @@ def predict(self, X, **predict_params):
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return pred_trans
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def _more_tags(self):
327-
regressor = self.regressor
328-
if regressor is None:
329-
from ..linear_model import LinearRegression
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regressor = LinearRegression()
358+
regressor = self._get_regressor()
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333360
return {
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"poor_score": True,
@@ -350,3 +377,31 @@ def n_features_in_(self):
350377
) from nfe
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352379
return self.regressor_.n_features_in_
380+
381+
def get_metadata_routing(self):
382+
"""Get metadata routing of this object.
383+
384+
Please check :ref:`User Guide <metadata_routing>` on how the routing
385+
mechanism works.
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387+
.. versionadded:: 1.6
388+
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Returns
390+
-------
391+
routing : MetadataRouter
392+
A :class:`~sklearn.utils.metadata_routing.MetadataRouter` encapsulating
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routing information.
394+
"""
395+
router = MetadataRouter(owner=self.__class__.__name__).add(
396+
regressor=self._get_regressor(),
397+
method_mapping=MethodMapping()
398+
.add(caller="fit", callee="fit")
399+
.add(caller="predict", callee="predict"),
400+
)
401+
return router
402+
403+
def _get_regressor(self, get_clone=False):
404+
if self.regressor is None:
405+
return LinearRegression()
406+
407+
return clone(self.regressor) if get_clone else self.regressor

‎sklearn/tests/test_metaestimators_metadata_routing.py

Copy file name to clipboardExpand all lines: sklearn/tests/test_metaestimators_metadata_routing.py
+8-1Lines changed: 8 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -382,6 +382,14 @@ def enable_slep006():
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"cv_name": "cv",
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"cv_routing_methods": ["fit"],
384384
},
385+
{
386+
"metaestimator": TransformedTargetRegressor,
387+
"estimator": "regressor",
388+
"estimator_name": "regressor",
389+
"X": X,
390+
"y": y,
391+
"estimator_routing_methods": ["fit", "predict"],
392+
},
385393
]
386394
"""List containing all metaestimators to be tested and their settings
387395
@@ -427,7 +435,6 @@ def enable_slep006():
427435
RFECV(ConsumingClassifier()),
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SelfTrainingClassifier(ConsumingClassifier()),
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SequentialFeatureSelector(ConsumingClassifier()),
430-
TransformedTargetRegressor(),
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]
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