
.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/miscellaneous/plot_metadata_routing.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_miscellaneous_plot_metadata_routing.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_miscellaneous_plot_metadata_routing.py:


=====================================================
Developing Estimators Compliant with Metadata Routing
=====================================================

.. currentmodule:: sklearn

This document shows how you can use the :ref:`metadata routing mechanism
<metadata_routing>` in scikit-learn to build estimators that route metadata
to other estimators, scorers, and CV splitters, that can consume :term:`metadata`.

To better understand the following document, we need to introduce two concepts:
:term:`routers <router>` and :term:`consumers <consumer>`. A :term:`router` is an object
which forwards some given data and metadata to other objects. In most cases, a router is
a :term:`meta-estimator`, i.e. an estimator which takes another estimator as a
parameter. A function such as :func:`sklearn.model_selection.cross_validate` which takes
an estimator as a parameter and forwards data and metadata, is also a router.

A :term:`consumer`, on the other hand, is an object which accepts and uses some given
metadata. For instance, an estimator taking into account ``sample_weight`` in
its :term:`fit` method is a consumer of ``sample_weight``.

It is possible for an object to be both a router and a consumer. For instance,
a meta-estimator may take into account ``sample_weight`` in certain
calculations, but it may also route it to the underlying estimator.

First a few imports and some random data for the rest of the script.

.. GENERATED FROM PYTHON SOURCE LINES 29-33

.. code-block:: Python


    # Authors: The scikit-learn developers
    # SPDX-License-Identifier: BSD-3-Clause








.. GENERATED FROM PYTHON SOURCE LINES 34-66

.. code-block:: Python


    import warnings
    from pprint import pprint

    import numpy as np

    from sklearn import set_config
    from sklearn.base import (
        BaseEstimator,
        ClassifierMixin,
        MetaEstimatorMixin,
        RegressorMixin,
        TransformerMixin,
        clone,
    )
    from sklearn.linear_model import LinearRegression
    from sklearn.utils import metadata_routing
    from sklearn.utils.metadata_routing import (
        MetadataRouter,
        MethodMapping,
        process_routing,
    )
    from sklearn.utils.validation import check_is_fitted

    n_samples, n_features = 100, 4
    rng = np.random.RandomState(42)
    X = rng.rand(n_samples, n_features)
    y = rng.randint(0, 2, size=n_samples)
    my_groups = rng.randint(0, 10, size=n_samples)
    my_weights = rng.rand(n_samples)
    my_other_weights = rng.rand(n_samples)








.. GENERATED FROM PYTHON SOURCE LINES 67-68

Metadata routing is only available if explicitly enabled:

.. GENERATED FROM PYTHON SOURCE LINES 68-71

.. code-block:: Python

    set_config(enable_metadata_routing=True)









.. GENERATED FROM PYTHON SOURCE LINES 72-73

This utility function is a dummy to check if a metadata is passed:

.. GENERATED FROM PYTHON SOURCE LINES 73-83

.. code-block:: Python

    def check_metadata(obj, **kwargs):
        for key, value in kwargs.items():
            if value is not None:
                print(
                    f"Received {key} of length = {len(value)} in {obj.__class__.__name__}."
                )
            else:
                print(f"{key} is None in {obj.__class__.__name__}.")









.. GENERATED FROM PYTHON SOURCE LINES 84-85

A utility function to nicely print the routing information of an object:

.. GENERATED FROM PYTHON SOURCE LINES 85-89

.. code-block:: Python

    def print_routing(obj):
        pprint(obj.get_metadata_routing()._serialize())









.. GENERATED FROM PYTHON SOURCE LINES 90-96

Consuming Estimator
-------------------
Here we demonstrate how an estimator can expose the required API to support
metadata routing as a consumer. Imagine a simple classifier accepting
``sample_weight`` as a metadata in its ``fit`` and ``groups`` in its
``predict`` method:

.. GENERATED FROM PYTHON SOURCE LINES 96-111

.. code-block:: Python



    class ExampleClassifier(ClassifierMixin, BaseEstimator):
        def fit(self, X, y, sample_weight=None):
            check_metadata(self, sample_weight=sample_weight)
            # all classifiers need to expose a classes_ attribute once they're fit.
            self.classes_ = np.array([0, 1])
            return self

        def predict(self, X, groups=None):
            check_metadata(self, groups=groups)
            # return a constant value of 1, not a very smart classifier!
            return np.ones(len(X))









.. GENERATED FROM PYTHON SOURCE LINES 112-122

The above estimator now has all it needs to consume metadata. This is
accomplished by some magic done in :class:`~base.BaseEstimator`. There are
now three methods exposed by the above class: ``set_fit_request``,
``set_predict_request``, and ``get_metadata_routing``. There is also a
``set_score_request`` for ``sample_weight`` which is present since
:class:`~base.ClassifierMixin` implements a ``score`` method accepting
``sample_weight``. The same applies to regressors which inherit from
:class:`~base.RegressorMixin`.

By default, no metadata is requested, which we can see as:

.. GENERATED FROM PYTHON SOURCE LINES 122-125

.. code-block:: Python


    print_routing(ExampleClassifier())





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'fit': {'sample_weight': None},
     'predict': {'groups': None},
     'score': {'sample_weight': None}}




.. GENERATED FROM PYTHON SOURCE LINES 126-132

The above output means that ``sample_weight`` and ``groups`` are not
requested by `ExampleClassifier`, and if a router is given those metadata, it
should raise an error, since the user has not explicitly set whether they are
required or not. The same is true for ``sample_weight`` in the ``score``
method, which is inherited from :class:`~base.ClassifierMixin`. In order to
explicitly set request values for those metadata, we can use these methods:

.. GENERATED FROM PYTHON SOURCE LINES 132-141

.. code-block:: Python


    est = (
        ExampleClassifier()
        .set_fit_request(sample_weight=False)
        .set_predict_request(groups=True)
        .set_score_request(sample_weight=False)
    )
    print_routing(est)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'fit': {'sample_weight': False},
     'predict': {'groups': True},
     'score': {'sample_weight': False}}




.. GENERATED FROM PYTHON SOURCE LINES 142-163

.. note ::
    Please note that as long as the above estimator is not used in a
    meta-estimator, the user does not need to set any requests for the
    metadata and the set values are ignored, since a consumer does not
    validate or route given metadata. A simple usage of the above estimator
    would work as expected.

    .. code-block:: python

        est = ExampleClassifier()
        est.fit(X, y, sample_weight=my_weights)
        est.predict(X[:3, :], groups=my_groups)

    Out:

    .. code-block:: python-console

        Received sample_weight of length = 100 in ExampleClassifier.
        Received groups of length = 100 in ExampleClassifier.

        array([1., 1., 1.])

.. GENERATED FROM PYTHON SOURCE LINES 165-177

Routing Meta-Estimator
----------------------
Now, we show how to design a meta-estimator to be a router. As a simplified
example, here is a meta-estimator, which doesn't do much other than routing
the metadata.

To make the meta-estimator a router, you only need to:

- define its `get_metadata_routing` method, which returns a `MetadataRouter`
  instance in charge of configuring the metadata routing.
- use `process_routing` inside its methods (`fit`, `predict`, ...) to  properly
  route the metadata from the meta-estimator to its sub-estimator.

.. GENERATED FROM PYTHON SOURCE LINES 177-216

.. code-block:: Python



    class MetaClassifier(MetaEstimatorMixin, ClassifierMixin, BaseEstimator):
        def __init__(self, estimator):
            self.estimator = estimator

        def get_metadata_routing(self):
            # This method defines the routing for this meta-estimator.
            # In order to do so, a `MetadataRouter` instance is created, and the
            # routing is added to it.
            router = MetadataRouter(owner=self).add(
                estimator=self.estimator,
                method_mapping=MethodMapping()
                .add(caller="fit", callee="fit")
                .add(caller="predict", callee="predict")
                .add(caller="score", callee="score"),
            )
            return router

        def fit(self, X, y, **fit_params):
            # Get information on all the metadata that should be routed from here to
            # consuming methods.
            routed_params = process_routing(self, "fit", **fit_params)
            # A sub-estimator is fitted and its classes are attributed to the
            # meta-estimator. Since we call the sub-estimator's fit method, we pass the
            # the metadata stored in `routed_params.estimator.fit`.
            self.estimator_ = clone(self.estimator).fit(X, y, **routed_params.estimator.fit)
            self.classes_ = self.estimator_.classes_
            return self

        def predict(self, X, **predict_params):
            check_is_fitted(self)
            # As in `fit`, we get information on all the metadata that should be routed and
            # pass the metadata that is stored in `routed_params.estimator.predict` to the
            # sub-estimator's predict method.
            routed_params = process_routing(self, "predict", **predict_params)
            return self.estimator_.predict(X, **routed_params.estimator.predict)









.. GENERATED FROM PYTHON SOURCE LINES 217-225

Let's break down different parts of the above code.

In each method, we use the ``process_routing`` function to construct a
:class:`~utils.Bunch` of the form ``{"object_name": {"method_name": {"metadata":
value}}}`` to pass to the underlying estimator's method. The ``object_name``
(``estimator`` in ``routed_params.estimator.fit``) is the same as the `estimator`
added in the ``get_metadata_routing``. ``process_routing`` also validates the input
metadata: it makes sure all given metadata are requested to avoid silent bugs.

.. GENERATED FROM PYTHON SOURCE LINES 227-229

Next, we illustrate the different behaviors and notably the type of errors
raised.

.. GENERATED FROM PYTHON SOURCE LINES 229-235

.. code-block:: Python


    meta_est = MetaClassifier(
        estimator=ExampleClassifier().set_fit_request(sample_weight=True)
    )
    meta_est.fit(X, y, sample_weight=my_weights)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in ExampleClassifier.


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>.sk-global {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: #000;
      --sklearn-color-text-muted: #666;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;
    }

    .sk-global.light {
      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: black;
      --sklearn-color-background: white;
      --sklearn-color-border-box: black;
      --sklearn-color-icon: #696969;
    }

    .sk-global.dark {
      --sklearn-color-text-on-default-background: white;
      --sklearn-color-background: #111;
      --sklearn-color-border-box: white;
      --sklearn-color-icon: #878787;
    }

    .sk-global {
      color: var(--sklearn-color-text);
    }

    .sk-global pre {
      padding: 0;
    }

    .sk-global input.sk-hidden--visually {
      border: 0;
      clip-path: inset(100%);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    .sk-global div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    .sk-global div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    .sk-global div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    .sk-global div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    .sk-global div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    .sk-global div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    .sk-global div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    .sk-global div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    .sk-global div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    .sk-global label.sk-toggleable__label {
      cursor: pointer;
      display: flex;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
    }

    .sk-global label.sk-toggleable__label .caption {
      font-size: 0.6rem;
      font-weight: lighter;
      color: var(--sklearn-color-text-muted);
    }

    .sk-global label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    .sk-global label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    .sk-global div.sk-toggleable__content {
      display: none;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      display: block;
      width: 100%;
      overflow: visible;
    }

    .sk-global input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    .sk-global div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    .sk-global div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .sk-global div.sk-label label.sk-toggleable__label,
    .sk-global div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    .sk-global div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    .sk-global div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    .sk-global div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      line-height: 1.2em;
    }

    .sk-global div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    .sk-global div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    .sk-global div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 0.5em;
      text-align: center;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-3) 1pt solid;
      color: var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3) 1pt solid;
      color: var(--sklearn-color-fitted-level-3);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-unfitted-level-0);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-fitted-level-0);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    .sk-global a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    .sk-global a.estimator_doc_link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    .sk-global a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    .sk-global a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }

    .sk-top-container.sk-global {
      /* pydata-sphinx-theme hides overflow, so scrolling is disabled.
       We need to set it to !important and add tabindex="0" in the HTML
       to allow keyboard-only users to navigate the display. */
      overflow-x: scroll !important;
      max-width: 100%;
    }

    .estimator-table {
        font-family: monospace;
    }

    .estimator-table summary {
        padding: .5rem;
        cursor: pointer;
    }

    .estimator-table summary::marker {
        font-size: 0.7rem;
    }

    .estimator-table details[open] {
        padding-left: 0.1rem;
        padding-right: 0.1rem;
        padding-bottom: 0.3rem;
    }

    .estimator-table .parameters-table {
        margin-left: auto !important;
        margin-right: auto !important;
        margin-top: 0;
    }

    .estimator-table .parameters-table tr:nth-child(odd) {
        background-color: #fff;
    }

    .estimator-table .parameters-table tr:nth-child(even) {
        background-color: #f6f6f6;
    }

    .estimator-table .parameters-table tr:hover td {
        background-color: #e0e0e0;
    }

    .estimator-table table :is(td, th) {
        border: 1px solid rgba(106, 105, 104, 0.232);
    }

    /*
        `table td`is set in notebook with right text-align.
        We need to overwrite it.
    */
    .estimator-table table td.param {
        text-align: left;
        position: relative;
        padding: 0;
    }

    .user-set td {
        color:rgb(255, 94, 0);
        text-align: left !important;
    }

    .user-set td.value {
        color:rgb(255, 94, 0);
        background-color: transparent;
    }

    .default td, .estimator-table th {
        color: black;
        text-align: left !important;
    }

    .user-set td i,
    .default td i {
        color: black;
    }

    td.fitted-att-type {
        white-space: preserve nowrap;
    }

    /*
        Styles for parameter documentation links
        We need styling for visited so jupyter doesn't overwrite it
    */
    a.param-doc-link,
    a.param-doc-link:link,
    a.param-doc-link:visited {
        text-decoration: underline dashed;
        text-underline-offset: .3em;
        color: inherit;
        display: block;
        padding: .5em;
    }

    @supports(anchor-name: --doc-link) {
        a.param-doc-link,
        a.param-doc-link:link,
        a.param-doc-link:visited {
        anchor-name: --doc-link;
        }
    }

    /* "hack" to make the entire area of the cell containing the link clickable */
    a.param-doc-link::before {
        position: absolute;
        content: "";
        inset: 0;
    }

    .param-doc-description {
        display: none;
        position: absolute;
        z-index: 9999;
        left: 0;
        padding: .5ex;
        margin-left: 1.5em;
        color: var(--sklearn-color-text);
        box-shadow: .3em .3em .4em #999;
        width: max-content;
        text-align: left;
        max-height: 10em;
        overflow-y: auto;

        /* unfitted */
        background: var(--sklearn-color-unfitted-level-0);
        border: thin solid var(--sklearn-color-unfitted-level-3);
    }

    @supports(position-area: center right) {
        .param-doc-description {
        position-area: center right;
        position: fixed;
        margin-left: 0;
        }
    }

    /* Fitted state for parameter tooltips */
    .fitted .param-doc-description {
        /* fitted */
        background: var(--sklearn-color-fitted-level-0);
        border: thin solid var(--sklearn-color-fitted-level-3);
    }

    .param-doc-link:hover .param-doc-description {
        display: block;
    }

    .copy-paste-icon {
        background-image: url(data:image/svg+xml;base64,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);
        background-repeat: no-repeat;
        background-size: 14px 14px;
        background-position: 0;
        display: inline-block;
        width: 14px;
        height: 14px;
        cursor: pointer;
    }

    .features {
      font-family: monospace;
      cursor: pointer;
      background-color: var(--sklearn-color-unfitted-level-0);
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: .20em;
      margin-bottom: 0.5em;
      font-size: inherit; /* Needed for jupyter */
    }

    .features.fitted {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features summary {
      cursor: pointer;
      display: flex;
      margin-bottom: 0;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
      padding: .25em;
    }

    .features details[open] > summary {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features.fitted details[open] > summary {
      background-color: var(--sklearn-color-fitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features details > summary .arrow::before {
      content: "▸";
      color: grey;
    }

    .features details[open] > summary .arrow::before {
      content: "▾";
    }

    .features details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .features.fitted details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .features .features-container {
      max-width: 15em;
      max-height: 10em;
      overflow: auto;
      scrollbar-width: thin;
      padding: .25em 0.1rem;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 0 0 .5em .5em;
    }

    .features.fitted .features-container {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features .image-container {
      block-size: 1em;
      inline-size: 1em;
      padding: 0;
      margin: 0%;
      display: flex;
      justify-content: center;
      align-items: center;
    }

    .features .copy-paste-icon {
      background-size: 1em 1em;
      width: 1em;
      height: 1em;
      filter: grayscale(100%) opacity(60%);
    }

    .features .features-container table {
      width: 100%;
      margin: 0.01em;
    }

    .features .features-container table tr:nth-child(odd) {
      background-color: #fff;
    }

    .features .features-container table tr:nth-child(even) {
      background-color: #f6f6f6;
    }

    .features .features-container table tr:hover {
      background-color: #e0e0e0;
    }

    .features .features-container table {
      table-layout: inherit;
    }

    .features .features-container table td {
      text-align: left;
      padding: 0 0.5em;
      border: 1px solid rgba(106, 105, 104, 0.232);
      white-space: nowrap;
      color: var(--sklearn-color-text);
    }

    .total_features {
      display: flex;
      justify-content: center;
      margin-top: 0.5em;
    }
    </style><body><div id="sk-container-id-26" tabindex="0" class="sk-top-container sk-global"><div class="sk-text-repr-fallback"><pre>MetaClassifier(estimator=ExampleClassifier())</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-78" type="checkbox" ><label for="sk-estimator-id-78" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>MetaClassifier</div></div><div><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></div></label><div class="sk-toggleable__content fitted" data-param-prefix="">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
            <tr class="user-set">
                <td><i class="copy-paste-icon"
                     onclick="copyToClipboard('estimator',
                              this.parentElement.nextElementSibling)"
                ></i></td>
                <td class="param">estimator</td>
                <td class="value">ExampleClassifier()</td>
            </tr>
    
                      </tbody>
                    </table>
                </details>
            </div>
    
            <div class="estimator-table">
                <details>
                    <summary>Fitted attributes</summary>
                    <table class="parameters-table">
                        <tbody>
                            <tr>
                            <th>Name</th>
                            <th>Type</th>
                            <th>Value</th>
                            </tr>
                        
           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">classes_</a></td>
               <td class="fitted-att-type">ndarray[int64](2,)</td>
               <td>[0,1]</td>


           </tr>
    

           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">estimator_</a></td>
               <td class="fitted-att-type">ExampleClassifier</td>
               <td>ExampleClassifier()</td>


           </tr>
    
                        </tbody>
                    </table>
                </details>
            </div>
        </div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-79" type="checkbox" ><label for="sk-estimator-id-79" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>estimator: ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__"><pre>ExampleClassifier()</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-80" type="checkbox" ><label for="sk-estimator-id-80" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
                      </tbody>
                    </table>
                </details>
            </div>
        </div></div></div></div></div></div></div></div></div></div><script>/*  Authors: The scikit-learn developers
     SPDX-License-Identifier: BSD-3-Clause
    */

    function copyToClipboard(text, element) {
        // Get the parameter prefix from the closest toggleable content
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
        const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;

        const originalStyle = element.style;
        const computedStyle = window.getComputedStyle(element);
        const originalWidth = computedStyle.width;
        const originalHTML = element.innerHTML.replace('Copied!', '');

        navigator.clipboard.writeText(fullParamName)
            .then(() => {
                element.style.width = originalWidth;
                element.style.color = 'green';
                element.innerHTML = "Copied!";

                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'red';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            });
        return false;
    }

    document.querySelectorAll('.copy-paste-icon').forEach(function(element) {
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';

        const parent = element.parentElement;
        if (!parent || !parent.nextElementSibling) {
            console.warn('Expected copy-paste icon is missing from the DOM structure');
            return;
        }

        const paramName = element.parentElement.nextElementSibling
            .textContent.trim().split(' ')[0];
        const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;

        element.setAttribute('title', fullParamName);
    });

    /**
     * Copy the list of feature names formatted as a Python list.
     *
     * @param {HTMLElement} element - The copy button inside a `.features` block; its siblings
     *   contain a `details` element and a table containing feature named.
     * @returns {boolean} Always returns `false` so callers can prevent the default click behavior.
     */
    function copyFeatureNamesToClipboard(element) {
        var detailsElem = element.closest('.features').querySelector('details');
        var wasOpen = detailsElem.open;
        detailsElem.open = true;
        var content = element.closest('.features').querySelector('tbody')
                      .innerText.trim();
        if (!wasOpen) detailsElem.open = false;
        const rows = content.split('\n').map(row => `    "${row}"`);
        const formattedText = `[\n${rows.join(',\n')},\n]`;
        const originalHTML = element.innerHTML.replace('✔', '');
        const originalStyle = element.style;
        const copyMark = document.createElement('span');
        copyMark.innerHTML = '✔';
        copyMark.style.color = 'blue';
        copyMark.style.fontSize = '1em';

        navigator.clipboard.writeText(formattedText)
            .then(() => {
                element.style.display = 'none';
                element.parentElement.appendChild(copyMark);

                setTimeout(() => {
                    copyMark.remove();
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'orange';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            });
        return false;
    }
    /**
     * Adapted from Skrub
     * https://github.com/skrub-data/skrub/blob/403466d1d5d4dc76a7ef569b3f8228db59a31dc3/skrub/_reporting/_data/templates/report.js#L789
     * @returns "light" or "dark"
     */
    function detectTheme(element) {
        const body = document.querySelector('body');

        // Check VSCode theme
        const themeKindAttr = body.getAttribute('data-vscode-theme-kind');
        const themeNameAttr = body.getAttribute('data-vscode-theme-name');

        if (themeKindAttr && themeNameAttr) {
            const themeKind = themeKindAttr.toLowerCase();
            const themeName = themeNameAttr.toLowerCase();

            if (themeKind.includes("dark") || themeName.includes("dark")) {
                return "dark";
            }
            if (themeKind.includes("light") || themeName.includes("light")) {
                return "light";
            }
        }

        // Check Jupyter theme
        if (body.getAttribute('data-jp-theme-light') === 'false') {
            return 'dark';
        } else if (body.getAttribute('data-jp-theme-light') === 'true') {
            return 'light';
        }

        // Guess based on a parent element's color
        const color = window.getComputedStyle(element.parentNode, null).getPropertyValue('color');
        const match = color.match(/^rgb\s*\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)\s*$/i);
        if (match) {
            const [r, g, b] = [
                parseFloat(match[1]),
                parseFloat(match[2]),
                parseFloat(match[3])
            ];

            // https://en.wikipedia.org/wiki/HSL_and_HSV#Lightness
            const luma = 0.299 * r + 0.587 * g + 0.114 * b;

            if (luma > 180) {
                // If the text is very bright we have a dark theme
                return 'dark';
            }
            if (luma < 75) {
                // If the text is very dark we have a light theme
                return 'light';
            }
            // Otherwise fall back to the next heuristic.
        }

        // Fallback to system preference
        return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
    }


    function forceTheme(elementId) {
        const estimatorElement = document.querySelector(`#${elementId}`);
        if (estimatorElement === null) {
            console.error(`Element with id ${elementId} not found.`);
        } else {
            const theme = detectTheme(estimatorElement);
            estimatorElement.classList.add(theme);
        }
    }

    forceTheme('sk-container-id-26');</script></body>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 236-240

Note that the above example is calling our utility function
`check_metadata()` via the `ExampleClassifier`. It checks that
``sample_weight`` is correctly passed to it. If it is not, like in the
following example, it would print that ``sample_weight`` is ``None``:

.. GENERATED FROM PYTHON SOURCE LINES 240-243

.. code-block:: Python


    meta_est.fit(X, y)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    sample_weight is None in ExampleClassifier.


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>.sk-global {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: #000;
      --sklearn-color-text-muted: #666;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;
    }

    .sk-global.light {
      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: black;
      --sklearn-color-background: white;
      --sklearn-color-border-box: black;
      --sklearn-color-icon: #696969;
    }

    .sk-global.dark {
      --sklearn-color-text-on-default-background: white;
      --sklearn-color-background: #111;
      --sklearn-color-border-box: white;
      --sklearn-color-icon: #878787;
    }

    .sk-global {
      color: var(--sklearn-color-text);
    }

    .sk-global pre {
      padding: 0;
    }

    .sk-global input.sk-hidden--visually {
      border: 0;
      clip-path: inset(100%);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    .sk-global div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    .sk-global div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    .sk-global div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    .sk-global div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    .sk-global div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    .sk-global div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    .sk-global div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    .sk-global div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    .sk-global div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    .sk-global label.sk-toggleable__label {
      cursor: pointer;
      display: flex;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
    }

    .sk-global label.sk-toggleable__label .caption {
      font-size: 0.6rem;
      font-weight: lighter;
      color: var(--sklearn-color-text-muted);
    }

    .sk-global label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    .sk-global label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    .sk-global div.sk-toggleable__content {
      display: none;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      display: block;
      width: 100%;
      overflow: visible;
    }

    .sk-global input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    .sk-global div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    .sk-global div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .sk-global div.sk-label label.sk-toggleable__label,
    .sk-global div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    .sk-global div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    .sk-global div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    .sk-global div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      line-height: 1.2em;
    }

    .sk-global div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    .sk-global div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    .sk-global div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 0.5em;
      text-align: center;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-3) 1pt solid;
      color: var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3) 1pt solid;
      color: var(--sklearn-color-fitted-level-3);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-unfitted-level-0);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-fitted-level-0);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    .sk-global a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    .sk-global a.estimator_doc_link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    .sk-global a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    .sk-global a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }

    .sk-top-container.sk-global {
      /* pydata-sphinx-theme hides overflow, so scrolling is disabled.
       We need to set it to !important and add tabindex="0" in the HTML
       to allow keyboard-only users to navigate the display. */
      overflow-x: scroll !important;
      max-width: 100%;
    }

    .estimator-table {
        font-family: monospace;
    }

    .estimator-table summary {
        padding: .5rem;
        cursor: pointer;
    }

    .estimator-table summary::marker {
        font-size: 0.7rem;
    }

    .estimator-table details[open] {
        padding-left: 0.1rem;
        padding-right: 0.1rem;
        padding-bottom: 0.3rem;
    }

    .estimator-table .parameters-table {
        margin-left: auto !important;
        margin-right: auto !important;
        margin-top: 0;
    }

    .estimator-table .parameters-table tr:nth-child(odd) {
        background-color: #fff;
    }

    .estimator-table .parameters-table tr:nth-child(even) {
        background-color: #f6f6f6;
    }

    .estimator-table .parameters-table tr:hover td {
        background-color: #e0e0e0;
    }

    .estimator-table table :is(td, th) {
        border: 1px solid rgba(106, 105, 104, 0.232);
    }

    /*
        `table td`is set in notebook with right text-align.
        We need to overwrite it.
    */
    .estimator-table table td.param {
        text-align: left;
        position: relative;
        padding: 0;
    }

    .user-set td {
        color:rgb(255, 94, 0);
        text-align: left !important;
    }

    .user-set td.value {
        color:rgb(255, 94, 0);
        background-color: transparent;
    }

    .default td, .estimator-table th {
        color: black;
        text-align: left !important;
    }

    .user-set td i,
    .default td i {
        color: black;
    }

    td.fitted-att-type {
        white-space: preserve nowrap;
    }

    /*
        Styles for parameter documentation links
        We need styling for visited so jupyter doesn't overwrite it
    */
    a.param-doc-link,
    a.param-doc-link:link,
    a.param-doc-link:visited {
        text-decoration: underline dashed;
        text-underline-offset: .3em;
        color: inherit;
        display: block;
        padding: .5em;
    }

    @supports(anchor-name: --doc-link) {
        a.param-doc-link,
        a.param-doc-link:link,
        a.param-doc-link:visited {
        anchor-name: --doc-link;
        }
    }

    /* "hack" to make the entire area of the cell containing the link clickable */
    a.param-doc-link::before {
        position: absolute;
        content: "";
        inset: 0;
    }

    .param-doc-description {
        display: none;
        position: absolute;
        z-index: 9999;
        left: 0;
        padding: .5ex;
        margin-left: 1.5em;
        color: var(--sklearn-color-text);
        box-shadow: .3em .3em .4em #999;
        width: max-content;
        text-align: left;
        max-height: 10em;
        overflow-y: auto;

        /* unfitted */
        background: var(--sklearn-color-unfitted-level-0);
        border: thin solid var(--sklearn-color-unfitted-level-3);
    }

    @supports(position-area: center right) {
        .param-doc-description {
        position-area: center right;
        position: fixed;
        margin-left: 0;
        }
    }

    /* Fitted state for parameter tooltips */
    .fitted .param-doc-description {
        /* fitted */
        background: var(--sklearn-color-fitted-level-0);
        border: thin solid var(--sklearn-color-fitted-level-3);
    }

    .param-doc-link:hover .param-doc-description {
        display: block;
    }

    .copy-paste-icon {
        background-image: url(data:image/svg+xml;base64,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);
        background-repeat: no-repeat;
        background-size: 14px 14px;
        background-position: 0;
        display: inline-block;
        width: 14px;
        height: 14px;
        cursor: pointer;
    }

    .features {
      font-family: monospace;
      cursor: pointer;
      background-color: var(--sklearn-color-unfitted-level-0);
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: .20em;
      margin-bottom: 0.5em;
      font-size: inherit; /* Needed for jupyter */
    }

    .features.fitted {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features summary {
      cursor: pointer;
      display: flex;
      margin-bottom: 0;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
      padding: .25em;
    }

    .features details[open] > summary {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features.fitted details[open] > summary {
      background-color: var(--sklearn-color-fitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features details > summary .arrow::before {
      content: "▸";
      color: grey;
    }

    .features details[open] > summary .arrow::before {
      content: "▾";
    }

    .features details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .features.fitted details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .features .features-container {
      max-width: 15em;
      max-height: 10em;
      overflow: auto;
      scrollbar-width: thin;
      padding: .25em 0.1rem;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 0 0 .5em .5em;
    }

    .features.fitted .features-container {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features .image-container {
      block-size: 1em;
      inline-size: 1em;
      padding: 0;
      margin: 0%;
      display: flex;
      justify-content: center;
      align-items: center;
    }

    .features .copy-paste-icon {
      background-size: 1em 1em;
      width: 1em;
      height: 1em;
      filter: grayscale(100%) opacity(60%);
    }

    .features .features-container table {
      width: 100%;
      margin: 0.01em;
    }

    .features .features-container table tr:nth-child(odd) {
      background-color: #fff;
    }

    .features .features-container table tr:nth-child(even) {
      background-color: #f6f6f6;
    }

    .features .features-container table tr:hover {
      background-color: #e0e0e0;
    }

    .features .features-container table {
      table-layout: inherit;
    }

    .features .features-container table td {
      text-align: left;
      padding: 0 0.5em;
      border: 1px solid rgba(106, 105, 104, 0.232);
      white-space: nowrap;
      color: var(--sklearn-color-text);
    }

    .total_features {
      display: flex;
      justify-content: center;
      margin-top: 0.5em;
    }
    </style><body><div id="sk-container-id-27" tabindex="0" class="sk-top-container sk-global"><div class="sk-text-repr-fallback"><pre>MetaClassifier(estimator=ExampleClassifier())</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-81" type="checkbox" ><label for="sk-estimator-id-81" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>MetaClassifier</div></div><div><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></div></label><div class="sk-toggleable__content fitted" data-param-prefix="">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
            <tr class="user-set">
                <td><i class="copy-paste-icon"
                     onclick="copyToClipboard('estimator',
                              this.parentElement.nextElementSibling)"
                ></i></td>
                <td class="param">estimator</td>
                <td class="value">ExampleClassifier()</td>
            </tr>
    
                      </tbody>
                    </table>
                </details>
            </div>
    
            <div class="estimator-table">
                <details>
                    <summary>Fitted attributes</summary>
                    <table class="parameters-table">
                        <tbody>
                            <tr>
                            <th>Name</th>
                            <th>Type</th>
                            <th>Value</th>
                            </tr>
                        
           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">classes_</a></td>
               <td class="fitted-att-type">ndarray[int64](2,)</td>
               <td>[0,1]</td>


           </tr>
    

           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">estimator_</a></td>
               <td class="fitted-att-type">ExampleClassifier</td>
               <td>ExampleClassifier()</td>


           </tr>
    
                        </tbody>
                    </table>
                </details>
            </div>
        </div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-82" type="checkbox" ><label for="sk-estimator-id-82" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>estimator: ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__"><pre>ExampleClassifier()</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-83" type="checkbox" ><label for="sk-estimator-id-83" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
                      </tbody>
                    </table>
                </details>
            </div>
        </div></div></div></div></div></div></div></div></div></div><script>/*  Authors: The scikit-learn developers
     SPDX-License-Identifier: BSD-3-Clause
    */

    function copyToClipboard(text, element) {
        // Get the parameter prefix from the closest toggleable content
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
        const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;

        const originalStyle = element.style;
        const computedStyle = window.getComputedStyle(element);
        const originalWidth = computedStyle.width;
        const originalHTML = element.innerHTML.replace('Copied!', '');

        navigator.clipboard.writeText(fullParamName)
            .then(() => {
                element.style.width = originalWidth;
                element.style.color = 'green';
                element.innerHTML = "Copied!";

                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'red';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            });
        return false;
    }

    document.querySelectorAll('.copy-paste-icon').forEach(function(element) {
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';

        const parent = element.parentElement;
        if (!parent || !parent.nextElementSibling) {
            console.warn('Expected copy-paste icon is missing from the DOM structure');
            return;
        }

        const paramName = element.parentElement.nextElementSibling
            .textContent.trim().split(' ')[0];
        const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;

        element.setAttribute('title', fullParamName);
    });

    /**
     * Copy the list of feature names formatted as a Python list.
     *
     * @param {HTMLElement} element - The copy button inside a `.features` block; its siblings
     *   contain a `details` element and a table containing feature named.
     * @returns {boolean} Always returns `false` so callers can prevent the default click behavior.
     */
    function copyFeatureNamesToClipboard(element) {
        var detailsElem = element.closest('.features').querySelector('details');
        var wasOpen = detailsElem.open;
        detailsElem.open = true;
        var content = element.closest('.features').querySelector('tbody')
                      .innerText.trim();
        if (!wasOpen) detailsElem.open = false;
        const rows = content.split('\n').map(row => `    "${row}"`);
        const formattedText = `[\n${rows.join(',\n')},\n]`;
        const originalHTML = element.innerHTML.replace('✔', '');
        const originalStyle = element.style;
        const copyMark = document.createElement('span');
        copyMark.innerHTML = '✔';
        copyMark.style.color = 'blue';
        copyMark.style.fontSize = '1em';

        navigator.clipboard.writeText(formattedText)
            .then(() => {
                element.style.display = 'none';
                element.parentElement.appendChild(copyMark);

                setTimeout(() => {
                    copyMark.remove();
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'orange';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            });
        return false;
    }
    /**
     * Adapted from Skrub
     * https://github.com/skrub-data/skrub/blob/403466d1d5d4dc76a7ef569b3f8228db59a31dc3/skrub/_reporting/_data/templates/report.js#L789
     * @returns "light" or "dark"
     */
    function detectTheme(element) {
        const body = document.querySelector('body');

        // Check VSCode theme
        const themeKindAttr = body.getAttribute('data-vscode-theme-kind');
        const themeNameAttr = body.getAttribute('data-vscode-theme-name');

        if (themeKindAttr && themeNameAttr) {
            const themeKind = themeKindAttr.toLowerCase();
            const themeName = themeNameAttr.toLowerCase();

            if (themeKind.includes("dark") || themeName.includes("dark")) {
                return "dark";
            }
            if (themeKind.includes("light") || themeName.includes("light")) {
                return "light";
            }
        }

        // Check Jupyter theme
        if (body.getAttribute('data-jp-theme-light') === 'false') {
            return 'dark';
        } else if (body.getAttribute('data-jp-theme-light') === 'true') {
            return 'light';
        }

        // Guess based on a parent element's color
        const color = window.getComputedStyle(element.parentNode, null).getPropertyValue('color');
        const match = color.match(/^rgb\s*\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)\s*$/i);
        if (match) {
            const [r, g, b] = [
                parseFloat(match[1]),
                parseFloat(match[2]),
                parseFloat(match[3])
            ];

            // https://en.wikipedia.org/wiki/HSL_and_HSV#Lightness
            const luma = 0.299 * r + 0.587 * g + 0.114 * b;

            if (luma > 180) {
                // If the text is very bright we have a dark theme
                return 'dark';
            }
            if (luma < 75) {
                // If the text is very dark we have a light theme
                return 'light';
            }
            // Otherwise fall back to the next heuristic.
        }

        // Fallback to system preference
        return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
    }


    function forceTheme(elementId) {
        const estimatorElement = document.querySelector(`#${elementId}`);
        if (estimatorElement === null) {
            console.error(`Element with id ${elementId} not found.`);
        } else {
            const theme = detectTheme(estimatorElement);
            estimatorElement.classList.add(theme);
        }
    }

    forceTheme('sk-container-id-27');</script></body>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 244-245

If we pass an unknown metadata, an error is raised:

.. GENERATED FROM PYTHON SOURCE LINES 245-250

.. code-block:: Python

    try:
        meta_est.fit(X, y, test=my_weights)
    except TypeError as e:
        print(e)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    MetaClassifier.fit got unexpected argument(s) {'test'}, which are not routed to any object.




.. GENERATED FROM PYTHON SOURCE LINES 251-252

And if we pass a metadata which is not explicitly requested:

.. GENERATED FROM PYTHON SOURCE LINES 252-257

.. code-block:: Python

    try:
        meta_est.fit(X, y, sample_weight=my_weights).predict(X, groups=my_groups)
    except ValueError as e:
        print(e)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in ExampleClassifier.
    [groups] are passed but are not explicitly set as requested or not requested for ExampleClassifier.predict, which is used within MetaClassifier.predict. Call `ExampleClassifier.set_predict_request({metadata}=True/False)` for each metadata you want to request/ignore. See the Metadata Routing User guide <https://scikit-learn.org/stable/metadata_routing.html> for more information.




.. GENERATED FROM PYTHON SOURCE LINES 258-259

Also, if we explicitly set it as not requested, but it is provided:

.. GENERATED FROM PYTHON SOURCE LINES 259-269

.. code-block:: Python

    meta_est = MetaClassifier(
        estimator=ExampleClassifier()
        .set_fit_request(sample_weight=True)
        .set_predict_request(groups=False)
    )
    try:
        meta_est.fit(X, y, sample_weight=my_weights).predict(X[:3, :], groups=my_groups)
    except TypeError as e:
        print(e)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in ExampleClassifier.
    MetaClassifier.predict got unexpected argument(s) {'groups'}, which are not routed to any object.




.. GENERATED FROM PYTHON SOURCE LINES 270-280

Another concept to introduce is **aliased metadata**. This is when an
estimator requests a metadata with a different variable name than the default
variable name. For instance, in a setting where there are two estimators in a
pipeline, one could request ``sample_weight1`` and the other
``sample_weight2``. Note that this doesn't change what the estimator expects,
it only tells the meta-estimator how to map the provided metadata to what is
required. Here's an example, where we pass ``aliased_sample_weight`` to the
meta-estimator, but the meta-estimator understands that
``aliased_sample_weight`` is an alias for ``sample_weight``, and passes it as
``sample_weight`` to the underlying estimator:

.. GENERATED FROM PYTHON SOURCE LINES 280-285

.. code-block:: Python

    meta_est = MetaClassifier(
        estimator=ExampleClassifier().set_fit_request(sample_weight="aliased_sample_weight")
    )
    meta_est.fit(X, y, aliased_sample_weight=my_weights)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in ExampleClassifier.


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>.sk-global {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: #000;
      --sklearn-color-text-muted: #666;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;
    }

    .sk-global.light {
      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: black;
      --sklearn-color-background: white;
      --sklearn-color-border-box: black;
      --sklearn-color-icon: #696969;
    }

    .sk-global.dark {
      --sklearn-color-text-on-default-background: white;
      --sklearn-color-background: #111;
      --sklearn-color-border-box: white;
      --sklearn-color-icon: #878787;
    }

    .sk-global {
      color: var(--sklearn-color-text);
    }

    .sk-global pre {
      padding: 0;
    }

    .sk-global input.sk-hidden--visually {
      border: 0;
      clip-path: inset(100%);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    .sk-global div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    .sk-global div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    .sk-global div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    .sk-global div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    .sk-global div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    .sk-global div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    .sk-global div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    .sk-global div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    .sk-global div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    .sk-global label.sk-toggleable__label {
      cursor: pointer;
      display: flex;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
    }

    .sk-global label.sk-toggleable__label .caption {
      font-size: 0.6rem;
      font-weight: lighter;
      color: var(--sklearn-color-text-muted);
    }

    .sk-global label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    .sk-global label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    .sk-global div.sk-toggleable__content {
      display: none;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      display: block;
      width: 100%;
      overflow: visible;
    }

    .sk-global input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    .sk-global div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    .sk-global div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .sk-global div.sk-label label.sk-toggleable__label,
    .sk-global div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    .sk-global div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    .sk-global div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    .sk-global div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      line-height: 1.2em;
    }

    .sk-global div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    .sk-global div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    .sk-global div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 0.5em;
      text-align: center;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-3) 1pt solid;
      color: var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3) 1pt solid;
      color: var(--sklearn-color-fitted-level-3);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-unfitted-level-0);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-fitted-level-0);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    .sk-global a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    .sk-global a.estimator_doc_link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    .sk-global a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    .sk-global a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }

    .sk-top-container.sk-global {
      /* pydata-sphinx-theme hides overflow, so scrolling is disabled.
       We need to set it to !important and add tabindex="0" in the HTML
       to allow keyboard-only users to navigate the display. */
      overflow-x: scroll !important;
      max-width: 100%;
    }

    .estimator-table {
        font-family: monospace;
    }

    .estimator-table summary {
        padding: .5rem;
        cursor: pointer;
    }

    .estimator-table summary::marker {
        font-size: 0.7rem;
    }

    .estimator-table details[open] {
        padding-left: 0.1rem;
        padding-right: 0.1rem;
        padding-bottom: 0.3rem;
    }

    .estimator-table .parameters-table {
        margin-left: auto !important;
        margin-right: auto !important;
        margin-top: 0;
    }

    .estimator-table .parameters-table tr:nth-child(odd) {
        background-color: #fff;
    }

    .estimator-table .parameters-table tr:nth-child(even) {
        background-color: #f6f6f6;
    }

    .estimator-table .parameters-table tr:hover td {
        background-color: #e0e0e0;
    }

    .estimator-table table :is(td, th) {
        border: 1px solid rgba(106, 105, 104, 0.232);
    }

    /*
        `table td`is set in notebook with right text-align.
        We need to overwrite it.
    */
    .estimator-table table td.param {
        text-align: left;
        position: relative;
        padding: 0;
    }

    .user-set td {
        color:rgb(255, 94, 0);
        text-align: left !important;
    }

    .user-set td.value {
        color:rgb(255, 94, 0);
        background-color: transparent;
    }

    .default td, .estimator-table th {
        color: black;
        text-align: left !important;
    }

    .user-set td i,
    .default td i {
        color: black;
    }

    td.fitted-att-type {
        white-space: preserve nowrap;
    }

    /*
        Styles for parameter documentation links
        We need styling for visited so jupyter doesn't overwrite it
    */
    a.param-doc-link,
    a.param-doc-link:link,
    a.param-doc-link:visited {
        text-decoration: underline dashed;
        text-underline-offset: .3em;
        color: inherit;
        display: block;
        padding: .5em;
    }

    @supports(anchor-name: --doc-link) {
        a.param-doc-link,
        a.param-doc-link:link,
        a.param-doc-link:visited {
        anchor-name: --doc-link;
        }
    }

    /* "hack" to make the entire area of the cell containing the link clickable */
    a.param-doc-link::before {
        position: absolute;
        content: "";
        inset: 0;
    }

    .param-doc-description {
        display: none;
        position: absolute;
        z-index: 9999;
        left: 0;
        padding: .5ex;
        margin-left: 1.5em;
        color: var(--sklearn-color-text);
        box-shadow: .3em .3em .4em #999;
        width: max-content;
        text-align: left;
        max-height: 10em;
        overflow-y: auto;

        /* unfitted */
        background: var(--sklearn-color-unfitted-level-0);
        border: thin solid var(--sklearn-color-unfitted-level-3);
    }

    @supports(position-area: center right) {
        .param-doc-description {
        position-area: center right;
        position: fixed;
        margin-left: 0;
        }
    }

    /* Fitted state for parameter tooltips */
    .fitted .param-doc-description {
        /* fitted */
        background: var(--sklearn-color-fitted-level-0);
        border: thin solid var(--sklearn-color-fitted-level-3);
    }

    .param-doc-link:hover .param-doc-description {
        display: block;
    }

    .copy-paste-icon {
        background-image: url(data:image/svg+xml;base64,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);
        background-repeat: no-repeat;
        background-size: 14px 14px;
        background-position: 0;
        display: inline-block;
        width: 14px;
        height: 14px;
        cursor: pointer;
    }

    .features {
      font-family: monospace;
      cursor: pointer;
      background-color: var(--sklearn-color-unfitted-level-0);
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: .20em;
      margin-bottom: 0.5em;
      font-size: inherit; /* Needed for jupyter */
    }

    .features.fitted {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features summary {
      cursor: pointer;
      display: flex;
      margin-bottom: 0;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
      padding: .25em;
    }

    .features details[open] > summary {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features.fitted details[open] > summary {
      background-color: var(--sklearn-color-fitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features details > summary .arrow::before {
      content: "▸";
      color: grey;
    }

    .features details[open] > summary .arrow::before {
      content: "▾";
    }

    .features details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .features.fitted details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .features .features-container {
      max-width: 15em;
      max-height: 10em;
      overflow: auto;
      scrollbar-width: thin;
      padding: .25em 0.1rem;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 0 0 .5em .5em;
    }

    .features.fitted .features-container {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features .image-container {
      block-size: 1em;
      inline-size: 1em;
      padding: 0;
      margin: 0%;
      display: flex;
      justify-content: center;
      align-items: center;
    }

    .features .copy-paste-icon {
      background-size: 1em 1em;
      width: 1em;
      height: 1em;
      filter: grayscale(100%) opacity(60%);
    }

    .features .features-container table {
      width: 100%;
      margin: 0.01em;
    }

    .features .features-container table tr:nth-child(odd) {
      background-color: #fff;
    }

    .features .features-container table tr:nth-child(even) {
      background-color: #f6f6f6;
    }

    .features .features-container table tr:hover {
      background-color: #e0e0e0;
    }

    .features .features-container table {
      table-layout: inherit;
    }

    .features .features-container table td {
      text-align: left;
      padding: 0 0.5em;
      border: 1px solid rgba(106, 105, 104, 0.232);
      white-space: nowrap;
      color: var(--sklearn-color-text);
    }

    .total_features {
      display: flex;
      justify-content: center;
      margin-top: 0.5em;
    }
    </style><body><div id="sk-container-id-28" tabindex="0" class="sk-top-container sk-global"><div class="sk-text-repr-fallback"><pre>MetaClassifier(estimator=ExampleClassifier())</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-84" type="checkbox" ><label for="sk-estimator-id-84" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>MetaClassifier</div></div><div><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></div></label><div class="sk-toggleable__content fitted" data-param-prefix="">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
            <tr class="user-set">
                <td><i class="copy-paste-icon"
                     onclick="copyToClipboard('estimator',
                              this.parentElement.nextElementSibling)"
                ></i></td>
                <td class="param">estimator</td>
                <td class="value">ExampleClassifier()</td>
            </tr>
    
                      </tbody>
                    </table>
                </details>
            </div>
    
            <div class="estimator-table">
                <details>
                    <summary>Fitted attributes</summary>
                    <table class="parameters-table">
                        <tbody>
                            <tr>
                            <th>Name</th>
                            <th>Type</th>
                            <th>Value</th>
                            </tr>
                        
           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">classes_</a></td>
               <td class="fitted-att-type">ndarray[int64](2,)</td>
               <td>[0,1]</td>


           </tr>
    

           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">estimator_</a></td>
               <td class="fitted-att-type">ExampleClassifier</td>
               <td>ExampleClassifier()</td>


           </tr>
    
                        </tbody>
                    </table>
                </details>
            </div>
        </div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-85" type="checkbox" ><label for="sk-estimator-id-85" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>estimator: ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__"><pre>ExampleClassifier()</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-86" type="checkbox" ><label for="sk-estimator-id-86" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
                      </tbody>
                    </table>
                </details>
            </div>
        </div></div></div></div></div></div></div></div></div></div><script>/*  Authors: The scikit-learn developers
     SPDX-License-Identifier: BSD-3-Clause
    */

    function copyToClipboard(text, element) {
        // Get the parameter prefix from the closest toggleable content
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
        const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;

        const originalStyle = element.style;
        const computedStyle = window.getComputedStyle(element);
        const originalWidth = computedStyle.width;
        const originalHTML = element.innerHTML.replace('Copied!', '');

        navigator.clipboard.writeText(fullParamName)
            .then(() => {
                element.style.width = originalWidth;
                element.style.color = 'green';
                element.innerHTML = "Copied!";

                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'red';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            });
        return false;
    }

    document.querySelectorAll('.copy-paste-icon').forEach(function(element) {
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';

        const parent = element.parentElement;
        if (!parent || !parent.nextElementSibling) {
            console.warn('Expected copy-paste icon is missing from the DOM structure');
            return;
        }

        const paramName = element.parentElement.nextElementSibling
            .textContent.trim().split(' ')[0];
        const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;

        element.setAttribute('title', fullParamName);
    });

    /**
     * Copy the list of feature names formatted as a Python list.
     *
     * @param {HTMLElement} element - The copy button inside a `.features` block; its siblings
     *   contain a `details` element and a table containing feature named.
     * @returns {boolean} Always returns `false` so callers can prevent the default click behavior.
     */
    function copyFeatureNamesToClipboard(element) {
        var detailsElem = element.closest('.features').querySelector('details');
        var wasOpen = detailsElem.open;
        detailsElem.open = true;
        var content = element.closest('.features').querySelector('tbody')
                      .innerText.trim();
        if (!wasOpen) detailsElem.open = false;
        const rows = content.split('\n').map(row => `    "${row}"`);
        const formattedText = `[\n${rows.join(',\n')},\n]`;
        const originalHTML = element.innerHTML.replace('✔', '');
        const originalStyle = element.style;
        const copyMark = document.createElement('span');
        copyMark.innerHTML = '✔';
        copyMark.style.color = 'blue';
        copyMark.style.fontSize = '1em';

        navigator.clipboard.writeText(formattedText)
            .then(() => {
                element.style.display = 'none';
                element.parentElement.appendChild(copyMark);

                setTimeout(() => {
                    copyMark.remove();
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'orange';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            });
        return false;
    }
    /**
     * Adapted from Skrub
     * https://github.com/skrub-data/skrub/blob/403466d1d5d4dc76a7ef569b3f8228db59a31dc3/skrub/_reporting/_data/templates/report.js#L789
     * @returns "light" or "dark"
     */
    function detectTheme(element) {
        const body = document.querySelector('body');

        // Check VSCode theme
        const themeKindAttr = body.getAttribute('data-vscode-theme-kind');
        const themeNameAttr = body.getAttribute('data-vscode-theme-name');

        if (themeKindAttr && themeNameAttr) {
            const themeKind = themeKindAttr.toLowerCase();
            const themeName = themeNameAttr.toLowerCase();

            if (themeKind.includes("dark") || themeName.includes("dark")) {
                return "dark";
            }
            if (themeKind.includes("light") || themeName.includes("light")) {
                return "light";
            }
        }

        // Check Jupyter theme
        if (body.getAttribute('data-jp-theme-light') === 'false') {
            return 'dark';
        } else if (body.getAttribute('data-jp-theme-light') === 'true') {
            return 'light';
        }

        // Guess based on a parent element's color
        const color = window.getComputedStyle(element.parentNode, null).getPropertyValue('color');
        const match = color.match(/^rgb\s*\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)\s*$/i);
        if (match) {
            const [r, g, b] = [
                parseFloat(match[1]),
                parseFloat(match[2]),
                parseFloat(match[3])
            ];

            // https://en.wikipedia.org/wiki/HSL_and_HSV#Lightness
            const luma = 0.299 * r + 0.587 * g + 0.114 * b;

            if (luma > 180) {
                // If the text is very bright we have a dark theme
                return 'dark';
            }
            if (luma < 75) {
                // If the text is very dark we have a light theme
                return 'light';
            }
            // Otherwise fall back to the next heuristic.
        }

        // Fallback to system preference
        return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
    }


    function forceTheme(elementId) {
        const estimatorElement = document.querySelector(`#${elementId}`);
        if (estimatorElement === null) {
            console.error(`Element with id ${elementId} not found.`);
        } else {
            const theme = detectTheme(estimatorElement);
            estimatorElement.classList.add(theme);
        }
    }

    forceTheme('sk-container-id-28');</script></body>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 286-288

Passing ``sample_weight`` here will fail since it is requested with an
alias and ``sample_weight`` with that name is not requested:

.. GENERATED FROM PYTHON SOURCE LINES 288-293

.. code-block:: Python

    try:
        meta_est.fit(X, y, sample_weight=my_weights)
    except TypeError as e:
        print(e)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    MetaClassifier.fit got unexpected argument(s) {'sample_weight'}, which are not routed to any object.




.. GENERATED FROM PYTHON SOURCE LINES 294-303

This leads us to the ``get_metadata_routing``. The way routing works in
scikit-learn is that consumers request what they need, and routers pass that
along. Additionally, a router exposes what it requires itself so that it can
be used inside another router, e.g. a pipeline inside a grid search object.
The output of the ``get_metadata_routing`` which is a dictionary
representation of a :class:`~utils.metadata_routing.MetadataRouter`, includes
the complete tree of requested metadata by all nested objects and their
corresponding method routings, i.e. which method of a sub-estimator is used
in which method of a meta-estimator:

.. GENERATED FROM PYTHON SOURCE LINES 303-306

.. code-block:: Python


    print_routing(meta_est)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'estimator': {'mapping': [{'callee': 'fit', 'caller': 'fit'},
                               {'callee': 'predict', 'caller': 'predict'},
                               {'callee': 'score', 'caller': 'score'}],
                   'router': {'fit': {'sample_weight': 'aliased_sample_weight'},
                              'predict': {'groups': None},
                              'score': {'sample_weight': None}}}}




.. GENERATED FROM PYTHON SOURCE LINES 307-315

As you can see, the only metadata requested for method ``fit`` is
``"sample_weight"`` with ``"aliased_sample_weight"`` as the alias. The
``~utils.metadata_routing.MetadataRouter`` class enables us to easily create
the routing object which would create the output we need for our
``get_metadata_routing``.

In order to understand how aliases work in meta-estimators, imagine our
meta-estimator inside another one:

.. GENERATED FROM PYTHON SOURCE LINES 315-320

.. code-block:: Python


    meta_meta_est = MetaClassifier(estimator=meta_est).fit(
        X, y, aliased_sample_weight=my_weights
    )





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in ExampleClassifier.




.. GENERATED FROM PYTHON SOURCE LINES 321-335

In the above example, this is how the ``fit`` method of `meta_meta_est`
will call their sub-estimator's ``fit`` methods::

    # user feeds `my_weights` as `aliased_sample_weight` into `meta_meta_est`:
    meta_meta_est.fit(X, y, aliased_sample_weight=my_weights):
        ...

        # the first sub-estimator (`meta_est`) expects `aliased_sample_weight`
        self.estimator_.fit(X, y, aliased_sample_weight=aliased_sample_weight):
            ...

            # the second sub-estimator (`est`) expects `sample_weight`
            self.estimator_.fit(X, y, sample_weight=aliased_sample_weight):
                ...

.. GENERATED FROM PYTHON SOURCE LINES 337-344

Consuming and routing Meta-Estimator
------------------------------------
For a slightly more complex example, consider a meta-estimator that routes
metadata to an underlying estimator as before, but it also uses some metadata
in its own methods. This meta-estimator is a consumer and a router at the
same time. Implementing one is very similar to what we had before, but with a
few tweaks.

.. GENERATED FROM PYTHON SOURCE LINES 344-389

.. code-block:: Python



    class RouterConsumerClassifier(MetaEstimatorMixin, ClassifierMixin, BaseEstimator):
        def __init__(self, estimator):
            self.estimator = estimator

        def get_metadata_routing(self):
            router = (
                MetadataRouter(owner=self)
                # defining metadata routing request values for usage in the meta-estimator
                .add_self_request(self)
                # defining metadata routing request values for usage in the sub-estimator
                .add(
                    estimator=self.estimator,
                    method_mapping=MethodMapping()
                    .add(caller="fit", callee="fit")
                    .add(caller="predict", callee="predict")
                    .add(caller="score", callee="score"),
                )
            )
            return router

        # Since `sample_weight` is used and consumed here, it should be defined as
        # an explicit argument in the method's signature. All other metadata which
        # are only routed, will be passed as `**fit_params`:
        def fit(self, X, y, sample_weight, **fit_params):
            if self.estimator is None:
                raise ValueError("estimator cannot be None!")

            check_metadata(self, sample_weight=sample_weight)

            # We add `sample_weight` to the `fit_params` dictionary.
            if sample_weight is not None:
                fit_params["sample_weight"] = sample_weight
            routed_params = process_routing(self, "fit", **fit_params)
            self.estimator_ = clone(self.estimator).fit(X, y, **routed_params.estimator.fit)
            self.classes_ = self.estimator_.classes_
            return self

        def predict(self, X, **predict_params):
            check_is_fitted(self)
            routed_params = process_routing(self, "predict", **predict_params)
            return self.estimator_.predict(X, **routed_params.estimator.predict)









.. GENERATED FROM PYTHON SOURCE LINES 390-402

The key parts where the above meta-estimator differs from our previous
meta-estimator is accepting ``sample_weight`` explicitly in ``fit`` and
including it in ``fit_params``. Since ``sample_weight`` is an explicit
argument, we can be sure that ``set_fit_request(sample_weight=...)`` is
present for this method. The meta-estimator is both a consumer, as well as a
router of ``sample_weight``.

In ``get_metadata_routing``, we add ``self`` to the routing using
``add_self_request`` to indicate this estimator is consuming
``sample_weight`` as well as being a router; which also adds a
``$self_request`` key to the routing info as illustrated below. Now let's
look at some examples:

.. GENERATED FROM PYTHON SOURCE LINES 404-405

- No metadata requested

.. GENERATED FROM PYTHON SOURCE LINES 405-409

.. code-block:: Python

    meta_est = RouterConsumerClassifier(estimator=ExampleClassifier())
    print_routing(meta_est)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'$self_request': {'fit': {'sample_weight': None},
                       'score': {'sample_weight': None}},
     'estimator': {'mapping': [{'callee': 'fit', 'caller': 'fit'},
                               {'callee': 'predict', 'caller': 'predict'},
                               {'callee': 'score', 'caller': 'score'}],
                   'router': {'fit': {'sample_weight': None},
                              'predict': {'groups': None},
                              'score': {'sample_weight': None}}}}




.. GENERATED FROM PYTHON SOURCE LINES 410-411

- ``sample_weight`` requested by sub-estimator

.. GENERATED FROM PYTHON SOURCE LINES 411-416

.. code-block:: Python

    meta_est = RouterConsumerClassifier(
        estimator=ExampleClassifier().set_fit_request(sample_weight=True)
    )
    print_routing(meta_est)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'$self_request': {'fit': {'sample_weight': None},
                       'score': {'sample_weight': None}},
     'estimator': {'mapping': [{'callee': 'fit', 'caller': 'fit'},
                               {'callee': 'predict', 'caller': 'predict'},
                               {'callee': 'score', 'caller': 'score'}],
                   'router': {'fit': {'sample_weight': True},
                              'predict': {'groups': None},
                              'score': {'sample_weight': None}}}}




.. GENERATED FROM PYTHON SOURCE LINES 417-418

- ``sample_weight`` requested by meta-estimator

.. GENERATED FROM PYTHON SOURCE LINES 418-423

.. code-block:: Python

    meta_est = RouterConsumerClassifier(estimator=ExampleClassifier()).set_fit_request(
        sample_weight=True
    )
    print_routing(meta_est)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'$self_request': {'fit': {'sample_weight': True},
                       'score': {'sample_weight': None}},
     'estimator': {'mapping': [{'callee': 'fit', 'caller': 'fit'},
                               {'callee': 'predict', 'caller': 'predict'},
                               {'callee': 'score', 'caller': 'score'}],
                   'router': {'fit': {'sample_weight': None},
                              'predict': {'groups': None},
                              'score': {'sample_weight': None}}}}




.. GENERATED FROM PYTHON SOURCE LINES 424-428

Note the difference in the requested metadata representations above.

- We can also alias the metadata to pass different values to the fit methods
  of the meta- and the sub-estimator:

.. GENERATED FROM PYTHON SOURCE LINES 428-434

.. code-block:: Python


    meta_est = RouterConsumerClassifier(
        estimator=ExampleClassifier().set_fit_request(sample_weight="clf_sample_weight"),
    ).set_fit_request(sample_weight="meta_clf_sample_weight")
    print_routing(meta_est)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'$self_request': {'fit': {'sample_weight': 'meta_clf_sample_weight'},
                       'score': {'sample_weight': None}},
     'estimator': {'mapping': [{'callee': 'fit', 'caller': 'fit'},
                               {'callee': 'predict', 'caller': 'predict'},
                               {'callee': 'score', 'caller': 'score'}],
                   'router': {'fit': {'sample_weight': 'clf_sample_weight'},
                              'predict': {'groups': None},
                              'score': {'sample_weight': None}}}}




.. GENERATED FROM PYTHON SOURCE LINES 435-438

However, ``fit`` of the meta-estimator only needs the alias for the
sub-estimator and addresses their own sample weight as `sample_weight`, since
it doesn't validate and route its own required metadata:

.. GENERATED FROM PYTHON SOURCE LINES 438-440

.. code-block:: Python

    meta_est.fit(X, y, sample_weight=my_weights, clf_sample_weight=my_other_weights)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in RouterConsumerClassifier.
    Received sample_weight of length = 100 in ExampleClassifier.


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>.sk-global {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: #000;
      --sklearn-color-text-muted: #666;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;
    }

    .sk-global.light {
      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: black;
      --sklearn-color-background: white;
      --sklearn-color-border-box: black;
      --sklearn-color-icon: #696969;
    }

    .sk-global.dark {
      --sklearn-color-text-on-default-background: white;
      --sklearn-color-background: #111;
      --sklearn-color-border-box: white;
      --sklearn-color-icon: #878787;
    }

    .sk-global {
      color: var(--sklearn-color-text);
    }

    .sk-global pre {
      padding: 0;
    }

    .sk-global input.sk-hidden--visually {
      border: 0;
      clip-path: inset(100%);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    .sk-global div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    .sk-global div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    .sk-global div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    .sk-global div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    .sk-global div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    .sk-global div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    .sk-global div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    .sk-global div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    .sk-global div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    .sk-global div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    .sk-global label.sk-toggleable__label {
      cursor: pointer;
      display: flex;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
    }

    .sk-global label.sk-toggleable__label .caption {
      font-size: 0.6rem;
      font-weight: lighter;
      color: var(--sklearn-color-text-muted);
    }

    .sk-global label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    .sk-global label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    .sk-global div.sk-toggleable__content {
      display: none;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .sk-global input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      display: block;
      width: 100%;
      overflow: visible;
    }

    .sk-global input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    .sk-global div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    .sk-global div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .sk-global div.sk-label label.sk-toggleable__label,
    .sk-global div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    .sk-global div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    .sk-global div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    .sk-global div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      line-height: 1.2em;
    }

    .sk-global div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    .sk-global div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    .sk-global div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    .sk-global div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .sk-global div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 0.5em;
      text-align: center;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-3) 1pt solid;
      color: var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3) 1pt solid;
      color: var(--sklearn-color-fitted-level-3);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-unfitted-level-0);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      border: var(--sklearn-color-fitted-level-0) 1pt solid;
      color: var(--sklearn-color-fitted-level-0);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    .sk-global a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    .sk-global a.estimator_doc_link.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    .sk-global a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    .sk-global a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }

    .sk-top-container.sk-global {
      /* pydata-sphinx-theme hides overflow, so scrolling is disabled.
       We need to set it to !important and add tabindex="0" in the HTML
       to allow keyboard-only users to navigate the display. */
      overflow-x: scroll !important;
      max-width: 100%;
    }

    .estimator-table {
        font-family: monospace;
    }

    .estimator-table summary {
        padding: .5rem;
        cursor: pointer;
    }

    .estimator-table summary::marker {
        font-size: 0.7rem;
    }

    .estimator-table details[open] {
        padding-left: 0.1rem;
        padding-right: 0.1rem;
        padding-bottom: 0.3rem;
    }

    .estimator-table .parameters-table {
        margin-left: auto !important;
        margin-right: auto !important;
        margin-top: 0;
    }

    .estimator-table .parameters-table tr:nth-child(odd) {
        background-color: #fff;
    }

    .estimator-table .parameters-table tr:nth-child(even) {
        background-color: #f6f6f6;
    }

    .estimator-table .parameters-table tr:hover td {
        background-color: #e0e0e0;
    }

    .estimator-table table :is(td, th) {
        border: 1px solid rgba(106, 105, 104, 0.232);
    }

    /*
        `table td`is set in notebook with right text-align.
        We need to overwrite it.
    */
    .estimator-table table td.param {
        text-align: left;
        position: relative;
        padding: 0;
    }

    .user-set td {
        color:rgb(255, 94, 0);
        text-align: left !important;
    }

    .user-set td.value {
        color:rgb(255, 94, 0);
        background-color: transparent;
    }

    .default td, .estimator-table th {
        color: black;
        text-align: left !important;
    }

    .user-set td i,
    .default td i {
        color: black;
    }

    td.fitted-att-type {
        white-space: preserve nowrap;
    }

    /*
        Styles for parameter documentation links
        We need styling for visited so jupyter doesn't overwrite it
    */
    a.param-doc-link,
    a.param-doc-link:link,
    a.param-doc-link:visited {
        text-decoration: underline dashed;
        text-underline-offset: .3em;
        color: inherit;
        display: block;
        padding: .5em;
    }

    @supports(anchor-name: --doc-link) {
        a.param-doc-link,
        a.param-doc-link:link,
        a.param-doc-link:visited {
        anchor-name: --doc-link;
        }
    }

    /* "hack" to make the entire area of the cell containing the link clickable */
    a.param-doc-link::before {
        position: absolute;
        content: "";
        inset: 0;
    }

    .param-doc-description {
        display: none;
        position: absolute;
        z-index: 9999;
        left: 0;
        padding: .5ex;
        margin-left: 1.5em;
        color: var(--sklearn-color-text);
        box-shadow: .3em .3em .4em #999;
        width: max-content;
        text-align: left;
        max-height: 10em;
        overflow-y: auto;

        /* unfitted */
        background: var(--sklearn-color-unfitted-level-0);
        border: thin solid var(--sklearn-color-unfitted-level-3);
    }

    @supports(position-area: center right) {
        .param-doc-description {
        position-area: center right;
        position: fixed;
        margin-left: 0;
        }
    }

    /* Fitted state for parameter tooltips */
    .fitted .param-doc-description {
        /* fitted */
        background: var(--sklearn-color-fitted-level-0);
        border: thin solid var(--sklearn-color-fitted-level-3);
    }

    .param-doc-link:hover .param-doc-description {
        display: block;
    }

    .copy-paste-icon {
        background-image: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCA0NDggNTEyIj48IS0tIUZvbnQgQXdlc29tZSBGcmVlIDYuNy4yIGJ5IEBmb250YXdlc29tZSAtIGh0dHBzOi8vZm9udGF3ZXNvbWUuY29tIExpY2Vuc2UgLSBodHRwczovL2ZvbnRhd2Vzb21lLmNvbS9saWNlbnNlL2ZyZWUgQ29weXJpZ2h0IDIwMjUgRm9udGljb25zLCBJbmMuLS0+PHBhdGggZD0iTTIwOCAwTDMzMi4xIDBjMTIuNyAwIDI0LjkgNS4xIDMzLjkgMTQuMWw2Ny45IDY3LjljOSA5IDE0LjEgMjEuMiAxNC4xIDMzLjlMNDQ4IDMzNmMwIDI2LjUtMjEuNSA0OC00OCA0OGwtMTkyIDBjLTI2LjUgMC00OC0yMS41LTQ4LTQ4bDAtMjg4YzAtMjYuNSAyMS41LTQ4IDQ4LTQ4ek00OCAxMjhsODAgMCAwIDY0LTY0IDAgMCAyNTYgMTkyIDAgMC0zMiA2NCAwIDAgNDhjMCAyNi41LTIxLjUgNDgtNDggNDhMNDggNTEyYy0yNi41IDAtNDgtMjEuNS00OC00OEwwIDE3NmMwLTI2LjUgMjEuNS00OCA0OC00OHoiLz48L3N2Zz4=);
        background-repeat: no-repeat;
        background-size: 14px 14px;
        background-position: 0;
        display: inline-block;
        width: 14px;
        height: 14px;
        cursor: pointer;
    }

    .features {
      font-family: monospace;
      cursor: pointer;
      background-color: var(--sklearn-color-unfitted-level-0);
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: .20em;
      margin-bottom: 0.5em;
      font-size: inherit; /* Needed for jupyter */
    }

    .features.fitted {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features summary {
      cursor: pointer;
      display: flex;
      margin-bottom: 0;
      text-align: center;
      align-items: center;
      justify-content: center;
      gap: 0.5em;
      padding: .25em;
    }

    .features details[open] > summary {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features.fitted details[open] > summary {
      background-color: var(--sklearn-color-fitted-level-2);
      border-radius: .20em 0 0 0;
    }

    .features details > summary .arrow::before {
      content: "▸";
      color: grey;
    }

    .features details[open] > summary .arrow::before {
      content: "▾";
    }

    .features details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    .features.fitted details:hover > summary {
      margin: 0;
      background-color: var(--sklearn-color-fitted-level-2);
    }

    .features .features-container {
      max-width: 15em;
      max-height: 10em;
      overflow: auto;
      scrollbar-width: thin;
      padding: .25em 0.1rem;
      background-color: var(--sklearn-color-unfitted-level-0);
      border-radius: 0 0 .5em .5em;
    }

    .features.fitted .features-container {
      background-color: var(--sklearn-color-fitted-level-0);
    }

    .features .image-container {
      block-size: 1em;
      inline-size: 1em;
      padding: 0;
      margin: 0%;
      display: flex;
      justify-content: center;
      align-items: center;
    }

    .features .copy-paste-icon {
      background-size: 1em 1em;
      width: 1em;
      height: 1em;
      filter: grayscale(100%) opacity(60%);
    }

    .features .features-container table {
      width: 100%;
      margin: 0.01em;
    }

    .features .features-container table tr:nth-child(odd) {
      background-color: #fff;
    }

    .features .features-container table tr:nth-child(even) {
      background-color: #f6f6f6;
    }

    .features .features-container table tr:hover {
      background-color: #e0e0e0;
    }

    .features .features-container table {
      table-layout: inherit;
    }

    .features .features-container table td {
      text-align: left;
      padding: 0 0.5em;
      border: 1px solid rgba(106, 105, 104, 0.232);
      white-space: nowrap;
      color: var(--sklearn-color-text);
    }

    .total_features {
      display: flex;
      justify-content: center;
      margin-top: 0.5em;
    }
    </style><body><div id="sk-container-id-29" tabindex="0" class="sk-top-container sk-global"><div class="sk-text-repr-fallback"><pre>RouterConsumerClassifier(estimator=ExampleClassifier())</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-87" type="checkbox" ><label for="sk-estimator-id-87" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>RouterConsumerClassifier</div></div><div><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></div></label><div class="sk-toggleable__content fitted" data-param-prefix="">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
            <tr class="user-set">
                <td><i class="copy-paste-icon"
                     onclick="copyToClipboard('estimator',
                              this.parentElement.nextElementSibling)"
                ></i></td>
                <td class="param">estimator</td>
                <td class="value">ExampleClassifier()</td>
            </tr>
    
                      </tbody>
                    </table>
                </details>
            </div>
    
            <div class="estimator-table">
                <details>
                    <summary>Fitted attributes</summary>
                    <table class="parameters-table">
                        <tbody>
                            <tr>
                            <th>Name</th>
                            <th>Type</th>
                            <th>Value</th>
                            </tr>
                        
           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">classes_</a></td>
               <td class="fitted-att-type">ndarray[int64](2,)</td>
               <td>[0,1]</td>


           </tr>
    

           <tr class="default">
               <td class="param"><a class="param-doc-link" style="text-decoration:none;">estimator_</a></td>
               <td class="fitted-att-type">ExampleClassifier</td>
               <td>ExampleClassifier()</td>


           </tr>
    
                        </tbody>
                    </table>
                </details>
            </div>
        </div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-88" type="checkbox" ><label for="sk-estimator-id-88" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>estimator: ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__"><pre>ExampleClassifier()</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually sk-global" id="sk-estimator-id-89" type="checkbox" ><label for="sk-estimator-id-89" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>ExampleClassifier</div></div></label><div class="sk-toggleable__content fitted" data-param-prefix="estimator__">
            <div class="estimator-table">
                <details>
                    <summary>Parameters</summary>
                    <table class="parameters-table">
                      <tbody>
                    
                      </tbody>
                    </table>
                </details>
            </div>
        </div></div></div></div></div></div></div></div></div></div><script>/*  Authors: The scikit-learn developers
     SPDX-License-Identifier: BSD-3-Clause
    */

    function copyToClipboard(text, element) {
        // Get the parameter prefix from the closest toggleable content
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
        const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;

        const originalStyle = element.style;
        const computedStyle = window.getComputedStyle(element);
        const originalWidth = computedStyle.width;
        const originalHTML = element.innerHTML.replace('Copied!', '');

        navigator.clipboard.writeText(fullParamName)
            .then(() => {
                element.style.width = originalWidth;
                element.style.color = 'green';
                element.innerHTML = "Copied!";

                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'red';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 2000);
            });
        return false;
    }

    document.querySelectorAll('.copy-paste-icon').forEach(function(element) {
        const toggleableContent = element.closest('.sk-toggleable__content');
        const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';

        const parent = element.parentElement;
        if (!parent || !parent.nextElementSibling) {
            console.warn('Expected copy-paste icon is missing from the DOM structure');
            return;
        }

        const paramName = element.parentElement.nextElementSibling
            .textContent.trim().split(' ')[0];
        const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;

        element.setAttribute('title', fullParamName);
    });

    /**
     * Copy the list of feature names formatted as a Python list.
     *
     * @param {HTMLElement} element - The copy button inside a `.features` block; its siblings
     *   contain a `details` element and a table containing feature named.
     * @returns {boolean} Always returns `false` so callers can prevent the default click behavior.
     */
    function copyFeatureNamesToClipboard(element) {
        var detailsElem = element.closest('.features').querySelector('details');
        var wasOpen = detailsElem.open;
        detailsElem.open = true;
        var content = element.closest('.features').querySelector('tbody')
                      .innerText.trim();
        if (!wasOpen) detailsElem.open = false;
        const rows = content.split('\n').map(row => `    "${row}"`);
        const formattedText = `[\n${rows.join(',\n')},\n]`;
        const originalHTML = element.innerHTML.replace('✔', '');
        const originalStyle = element.style;
        const copyMark = document.createElement('span');
        copyMark.innerHTML = '✔';
        copyMark.style.color = 'blue';
        copyMark.style.fontSize = '1em';

        navigator.clipboard.writeText(formattedText)
            .then(() => {
                element.style.display = 'none';
                element.parentElement.appendChild(copyMark);

                setTimeout(() => {
                    copyMark.remove();
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            })
            .catch(err => {
                console.error('Failed to copy:', err);
                element.style.color = 'orange';
                element.innerHTML = "Failed!";
                setTimeout(() => {
                    element.innerHTML = originalHTML;
                    element.style = originalStyle;
                }, 1000);
            });
        return false;
    }
    /**
     * Adapted from Skrub
     * https://github.com/skrub-data/skrub/blob/403466d1d5d4dc76a7ef569b3f8228db59a31dc3/skrub/_reporting/_data/templates/report.js#L789
     * @returns "light" or "dark"
     */
    function detectTheme(element) {
        const body = document.querySelector('body');

        // Check VSCode theme
        const themeKindAttr = body.getAttribute('data-vscode-theme-kind');
        const themeNameAttr = body.getAttribute('data-vscode-theme-name');

        if (themeKindAttr && themeNameAttr) {
            const themeKind = themeKindAttr.toLowerCase();
            const themeName = themeNameAttr.toLowerCase();

            if (themeKind.includes("dark") || themeName.includes("dark")) {
                return "dark";
            }
            if (themeKind.includes("light") || themeName.includes("light")) {
                return "light";
            }
        }

        // Check Jupyter theme
        if (body.getAttribute('data-jp-theme-light') === 'false') {
            return 'dark';
        } else if (body.getAttribute('data-jp-theme-light') === 'true') {
            return 'light';
        }

        // Guess based on a parent element's color
        const color = window.getComputedStyle(element.parentNode, null).getPropertyValue('color');
        const match = color.match(/^rgb\s*\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)\s*$/i);
        if (match) {
            const [r, g, b] = [
                parseFloat(match[1]),
                parseFloat(match[2]),
                parseFloat(match[3])
            ];

            // https://en.wikipedia.org/wiki/HSL_and_HSV#Lightness
            const luma = 0.299 * r + 0.587 * g + 0.114 * b;

            if (luma > 180) {
                // If the text is very bright we have a dark theme
                return 'dark';
            }
            if (luma < 75) {
                // If the text is very dark we have a light theme
                return 'light';
            }
            // Otherwise fall back to the next heuristic.
        }

        // Fallback to system preference
        return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
    }


    function forceTheme(elementId) {
        const estimatorElement = document.querySelector(`#${elementId}`);
        if (estimatorElement === null) {
            console.error(`Element with id ${elementId} not found.`);
        } else {
            const theme = detectTheme(estimatorElement);
            estimatorElement.classList.add(theme);
        }
    }

    forceTheme('sk-container-id-29');</script></body>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 441-445

- Alias only on the sub-estimator:

This is useful when we don't want the meta-estimator to use the metadata, but
the sub-estimator should.

.. GENERATED FROM PYTHON SOURCE LINES 445-449

.. code-block:: Python

    meta_est = RouterConsumerClassifier(
        estimator=ExampleClassifier().set_fit_request(sample_weight="aliased_sample_weight")
    )
    print_routing(meta_est)




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    {'$self_request': {'fit': {'sample_weight': None},
                       'score': {'sample_weight': None}},
     'estimator': {'mapping': [{'callee': 'fit', 'caller': 'fit'},
                               {'callee': 'predict', 'caller': 'predict'},
                               {'callee': 'score', 'caller': 'score'}],
                   'router': {'fit': {'sample_weight': 'aliased_sample_weight'},
                              'predict': {'groups': None},
                              'score': {'sample_weight': None}}}}




.. GENERATED FROM PYTHON SOURCE LINES 450-453

The meta-estimator cannot use `aliased_sample_weight`, because it expects
it passed as `sample_weight`. This would apply even if
`set_fit_request(sample_weight=True)` was set on it.

.. GENERATED FROM PYTHON SOURCE LINES 455-464

Simple Pipeline
---------------
A slightly more complicated use-case is a meta-estimator resembling a
:class:`~pipeline.Pipeline`. Here is a meta-estimator, which accepts a
transformer and a classifier. When calling its `fit` method, it applies the
transformer's `fit` and `transform` before running the classifier on the
transformed data. Upon `predict`, it applies the transformer's `transform`
before predicting with the classifier's `predict` method on the transformed
new data.

.. GENERATED FROM PYTHON SOURCE LINES 464-521

.. code-block:: Python



    class SimplePipeline(ClassifierMixin, BaseEstimator):
        def __init__(self, transformer, classifier):
            self.transformer = transformer
            self.classifier = classifier

        def get_metadata_routing(self):
            router = (
                MetadataRouter(owner=self)
                # We add the routing for the transformer.
                .add(
                    transformer=self.transformer,
                    method_mapping=MethodMapping()
                    # The metadata is routed such that it retraces how
                    # `SimplePipeline` internally calls the transformer's `fit` and
                    # `transform` methods in its own methods (`fit` and `predict`).
                    .add(caller="fit", callee="fit")
                    .add(caller="fit", callee="transform")
                    .add(caller="predict", callee="transform"),
                )
                # We add the routing for the classifier.
                .add(
                    classifier=self.classifier,
                    method_mapping=MethodMapping()
                    .add(caller="fit", callee="fit")
                    .add(caller="predict", callee="predict"),
                )
            )
            return router

        def fit(self, X, y, **fit_params):
            routed_params = process_routing(self, "fit", **fit_params)

            self.transformer_ = clone(self.transformer).fit(
                X, y, **routed_params.transformer.fit
            )
            X_transformed = self.transformer_.transform(
                X, **routed_params.transformer.transform
            )

            self.classifier_ = clone(self.classifier).fit(
                X_transformed, y, **routed_params.classifier.fit
            )
            return self

        def predict(self, X, **predict_params):
            routed_params = process_routing(self, "predict", **predict_params)

            X_transformed = self.transformer_.transform(
                X, **routed_params.transformer.transform
            )
            return self.classifier_.predict(
                X_transformed, **routed_params.classifier.predict
            )









.. GENERATED FROM PYTHON SOURCE LINES 522-538

Note the usage of :class:`~utils.metadata_routing.MethodMapping` to
declare which methods of the child estimator (callee) are used in which
methods of the meta estimator (caller). As you can see, `SimplePipeline` uses
the transformer's ``transform`` and ``fit`` methods in ``fit``, and its
``transform`` method in ``predict``, and that's what you see implemented in
the routing structure of the pipeline class.

Another difference in the above example with the previous ones is the usage
of :func:`~utils.metadata_routing.process_routing`, which processes the input
parameters, does the required validation, and returns the `routed_params`
which we had created in previous examples. This reduces the boilerplate code
a developer needs to write in each meta-estimator's method. Developers are
strongly recommended to use this function unless there is a good reason
against it.

In order to test the above pipeline, let's add an example transformer.

.. GENERATED FROM PYTHON SOURCE LINES 538-553

.. code-block:: Python



    class ExampleTransformer(TransformerMixin, BaseEstimator):
        def fit(self, X, y, sample_weight=None):
            check_metadata(self, sample_weight=sample_weight)
            return self

        def transform(self, X, groups=None):
            check_metadata(self, groups=groups)
            return X

        def fit_transform(self, X, y, sample_weight=None, groups=None):
            return self.fit(X, y, sample_weight).transform(X, groups)









.. GENERATED FROM PYTHON SOURCE LINES 554-563

Note that in the above example, we have implemented ``fit_transform`` which
calls ``fit`` and ``transform`` with the appropriate metadata. This is only
required if ``transform`` accepts metadata, since the default ``fit_transform``
implementation in :class:`~base.TransformerMixin` doesn't pass metadata to
``transform``.

Now we can test our pipeline, and see if metadata is correctly passed around.
This example uses our `SimplePipeline`, our `ExampleTransformer`, and our
`RouterConsumerClassifier` which uses our `ExampleClassifier`.

.. GENERATED FROM PYTHON SOURCE LINES 563-584

.. code-block:: Python


    pipe = SimplePipeline(
        transformer=ExampleTransformer()
        # we set transformer's fit to receive sample_weight
        .set_fit_request(sample_weight=True)
        # we set transformer's transform to receive groups
        .set_transform_request(groups=True),
        classifier=RouterConsumerClassifier(
            estimator=ExampleClassifier()
            # we want this sub-estimator to receive sample_weight in fit
            .set_fit_request(sample_weight=True)
            # but not groups in predict
            .set_predict_request(groups=False),
        )
        # and we want the meta-estimator to receive sample_weight as well
        .set_fit_request(sample_weight=True),
    )
    pipe.fit(X, y, sample_weight=my_weights, groups=my_groups).predict(
        X[:3], groups=my_groups
    )





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in ExampleTransformer.
    Received groups of length = 100 in ExampleTransformer.
    Received sample_weight of length = 100 in RouterConsumerClassifier.
    Received sample_weight of length = 100 in ExampleClassifier.
    Received groups of length = 100 in ExampleTransformer.
    groups is None in ExampleClassifier.

    array([1., 1., 1.])



.. GENERATED FROM PYTHON SOURCE LINES 585-592

Deprecation / Default Value Change
----------------------------------
In this section we show how one should handle the case where a router becomes
also a consumer, especially when it consumes the same metadata as its
sub-estimator, or a consumer starts consuming a metadata which it wasn't in
an older release. In this case, a warning should be raised for a while, to
let users know the behavior is changed from previous versions.

.. GENERATED FROM PYTHON SOURCE LINES 592-610

.. code-block:: Python



    class MetaRegressor(MetaEstimatorMixin, RegressorMixin, BaseEstimator):
        def __init__(self, estimator):
            self.estimator = estimator

        def fit(self, X, y, **fit_params):
            routed_params = process_routing(self, "fit", **fit_params)
            self.estimator_ = clone(self.estimator).fit(X, y, **routed_params.estimator.fit)

        def get_metadata_routing(self):
            router = MetadataRouter(owner=self).add(
                estimator=self.estimator,
                method_mapping=MethodMapping().add(caller="fit", callee="fit"),
            )
            return router









.. GENERATED FROM PYTHON SOURCE LINES 611-613

As explained above, this is a valid usage if `my_weights` aren't supposed
to be passed as `sample_weight` to `MetaRegressor`:

.. GENERATED FROM PYTHON SOURCE LINES 613-618

.. code-block:: Python


    reg = MetaRegressor(estimator=LinearRegression().set_fit_request(sample_weight=True))
    reg.fit(X, y, sample_weight=my_weights)









.. GENERATED FROM PYTHON SOURCE LINES 619-621

Now imagine we further develop ``MetaRegressor`` and it now also *consumes*
``sample_weight``:

.. GENERATED FROM PYTHON SOURCE LINES 621-650

.. code-block:: Python



    class WeightedMetaRegressor(MetaEstimatorMixin, RegressorMixin, BaseEstimator):
        # show warning to remind user to explicitly set the value with
        # `.set_{method}_request(sample_weight={boolean})`
        __metadata_request__fit = {"sample_weight": metadata_routing.WARN}

        def __init__(self, estimator):
            self.estimator = estimator

        def fit(self, X, y, sample_weight=None, **fit_params):
            routed_params = process_routing(
                self, "fit", sample_weight=sample_weight, **fit_params
            )
            check_metadata(self, sample_weight=sample_weight)
            self.estimator_ = clone(self.estimator).fit(X, y, **routed_params.estimator.fit)

        def get_metadata_routing(self):
            router = (
                MetadataRouter(owner=self)
                .add_self_request(self)
                .add(
                    estimator=self.estimator,
                    method_mapping=MethodMapping().add(caller="fit", callee="fit"),
                )
            )
            return router









.. GENERATED FROM PYTHON SOURCE LINES 651-654

The above implementation is almost the same as ``MetaRegressor``, and
because of the default request value defined in ``__metadata_request__fit``
there is a warning raised when fitted.

.. GENERATED FROM PYTHON SOURCE LINES 654-663

.. code-block:: Python


    with warnings.catch_warnings(record=True) as record:
        WeightedMetaRegressor(
            estimator=LinearRegression().set_fit_request(sample_weight=False)
        ).fit(X, y, sample_weight=my_weights)
    for w in record:
        print(w.message)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Received sample_weight of length = 100 in WeightedMetaRegressor.
    Support for sample_weight has recently been added to WeightedMetaRegressor(estimator=LinearRegression()) class. To maintain backward compatibility, it is ignored now. Using `set_fit_request(sample_weight={True, False})` on this method of the class, you can set the request value to False to silence this warning, or to True to consume and use the metadata.




.. GENERATED FROM PYTHON SOURCE LINES 664-666

When an estimator consumes a metadata which it didn't consume before, the
following pattern can be used to warn the users about it.

.. GENERATED FROM PYTHON SOURCE LINES 666-684

.. code-block:: Python



    class ExampleRegressor(RegressorMixin, BaseEstimator):
        __metadata_request__fit = {"sample_weight": metadata_routing.WARN}

        def fit(self, X, y, sample_weight=None):
            check_metadata(self, sample_weight=sample_weight)
            return self

        def predict(self, X):
            return np.zeros(shape=(len(X)))


    with warnings.catch_warnings(record=True) as record:
        MetaRegressor(estimator=ExampleRegressor()).fit(X, y, sample_weight=my_weights)
    for w in record:
        print(w.message)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    sample_weight is None in ExampleRegressor.
    Support for sample_weight has recently been added to ExampleRegressor() class. To maintain backward compatibility, it is ignored now. Using `set_fit_request(sample_weight={True, False})` on this method of the class, you can set the request value to False to silence this warning, or to True to consume and use the metadata.




.. GENERATED FROM PYTHON SOURCE LINES 685-686

At the end we disable the configuration flag for metadata routing:

.. GENERATED FROM PYTHON SOURCE LINES 686-689

.. code-block:: Python


    set_config(enable_metadata_routing=False)








.. GENERATED FROM PYTHON SOURCE LINES 690-707

Third Party Development and scikit-learn Dependency
---------------------------------------------------

As seen above, information is communicated between classes using
:class:`~utils.metadata_routing.MetadataRequest` and
:class:`~utils.metadata_routing.MetadataRouter`. It is strongly not advised,
but possible to vendor the tools related to metadata-routing if you strictly
want to have a scikit-learn compatible estimator, without depending on the
scikit-learn package. If all of the following conditions are met, you do NOT
need to modify your code at all:

- your estimator inherits from :class:`~base.BaseEstimator`
- the parameters consumed by your estimator's methods, e.g. ``fit``, are
  explicitly defined in the method's signature, as opposed to being
  ``*args`` or ``*kwargs``.
- your estimator does not route any metadata to the underlying objects, i.e.
  it's not a *router*.


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.035 seconds)


.. _sphx_glr_download_auto_examples_miscellaneous_plot_metadata_routing.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_metadata_routing.ipynb <plot_metadata_routing.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_metadata_routing.py <plot_metadata_routing.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_metadata_routing.zip <plot_metadata_routing.zip>`


.. include:: plot_metadata_routing.recommendations


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_
