.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/developing_estimators/sklearn_is_fitted.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_developing_estimators_sklearn_is_fitted.py>`
        to download the full example code. or to run this example in your browser via Binder

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

.. _sphx_glr_auto_examples_developing_estimators_sklearn_is_fitted.py:


========================================
 `__sklearn_is_fitted__` 作为开发者 API
========================================

 `__sklearn_is_fitted__` 方法是 scikit-learn 中用于检查估计器对象是否已被拟合的约定。这个方法通常在基于 scikit-learn 基类（如 `BaseEstimator` 或其子类）构建的自定义估计器类中实现。

开发者应在除 `fit` 之外的所有方法的开头使用 :func:`~sklearn.utils.validation.check_is_fitted` 。如果他们需要自定义或加速检查过程，可以按照下面的示例实现 `__sklearn_is_fitted__` 方法。

在这个示例中，自定义估计器展示了 `__sklearn_is_fitted__` 方法和 `check_is_fitted` 实用函数作为开发者 API 的用法。 `__sklearn_is_fitted__` 方法通过验证 `_is_fitted` 属性的存在来检查是否已拟合。

.. GENERATED FROM PYTHON SOURCE LINES 14-19

一个实现简单分类器的自定义估计器示例
----------------------------------------
此代码片段定义了一个名为 `CustomEstimator` 的自定义估计器类，
该类继承自 scikit-learn 的 `BaseEstimator` 和 `ClassifierMixin` 类，
并展示了 `__sklearn_is_fitted__` 方法和 `check_is_fitted` 实用函数的用法。

.. GENERATED FROM PYTHON SOURCE LINES 19-65

.. code-block:: Python



    # 作者：scikit-learn 开发者
    # SPDX-License-Identifier: BSD-3-Clause

    from sklearn.base import BaseEstimator, ClassifierMixin
    from sklearn.utils.validation import check_is_fitted


    class CustomEstimator(BaseEstimator, ClassifierMixin):
        def __init__(self, parameter=1):
            self.parameter = parameter

        def fit(self, X, y):
            """
            将估计器拟合到训练数据。
            """
            self.classes_ = sorted(set(y))
            # 自定义属性以跟踪估计器是否已拟合
            self._is_fitted = True
            return self

        def predict(self, X):
            """进行预测

    如果估计器未拟合，则引发 NotFittedError
    """
            check_is_fitted(self)
            # 执行预测逻辑
            predictions = [self.classes_[0]] * len(X)
            return predictions

        def score(self, X, y):
            """计算分数

    如果估算器未拟合，则引发 NotFittedError
    """
            check_is_fitted(self)
            # 执行评分逻辑
            return 0.5

        def __sklearn_is_fitted__(self):
            """
            检查拟合状态并返回布尔值。
            """
            return hasattr(self, "_is_fitted") and self._is_fitted


.. _sphx_glr_download_auto_examples_developing_estimators_sklearn_is_fitted.py:

.. only:: html

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

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/scikit-learn/scikit-learn/main?urlpath=lab/tree/notebooks/auto_examples/developing_estimators/sklearn_is_fitted.ipynb
        :alt: Launch binder
        :width: 150 px

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

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

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

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

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

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


.. include:: sklearn_is_fitted.recommendations


.. only:: html

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

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