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

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

.. _sphx_glr_auto_examples_miscellaneous_plot_roc_curve_visualization_api.py:


=============================================
منحنى ROC مع واجهة برمجة التطبيقات للتصور
=============================================
يعرّف Scikit-learn واجهة برمجة تطبيقات بسيطة لإنشاء تصورات للتعلم الآلي. الميزات الرئيسية لهذه الواجهة هي السماح بالرسم السريع والتعديلات المرئية دون إعادة الحساب. في هذا المثال، سوف نوضح كيفية استخدام واجهة برمجة التطبيقات للتصور من خلال مقارنة منحنيات ROC.

.. GENERATED FROM PYTHON SOURCE LINES 8-12

.. code-block:: Python


    # المؤلفون: مطوري scikit-learn
    # معرف SPDX-License: BSD-3-Clause








.. GENERATED FROM PYTHON SOURCE LINES 13-16

تحميل البيانات وتدريب SVC
-------------------------
أولاً، نقوم بتحميل مجموعة بيانات النبيذ وتحويلها إلى مشكلة تصنيف ثنائي. ثم نقوم بتدريب مصنف ناقل الدعم على مجموعة بيانات التدريب.

.. GENERATED FROM PYTHON SOURCE LINES 16-31

.. code-block:: Python

    import matplotlib.pyplot as plt

    from sklearn.datasets import load_wine
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.metrics import RocCurveDisplay
    from sklearn.model_selection import train_test_split
    from sklearn.svm import SVC

    X, y = load_wine(return_X_y=True)
    y = y == 2

    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)
    svc = SVC(random_state=42)
    svc.fit(X_train, y_train)






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
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      /* 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;

      /* Specific color for light theme */
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      --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
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      --sklearn-color-icon: #696969;

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        /* Redefinition of color scheme for dark theme */
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        --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
        --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
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    #sk-container-id-35 div.sk-dashed-wrapped {
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      /* 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-container-id-35 div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
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      background-repeat: no-repeat;
      background-position: center center;
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    #sk-container-id-35 div.sk-parallel-item {
      display: flex;
      flex-direction: column;
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    #sk-container-id-35 div.sk-parallel-item:first-child::after {
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      width: 50%;
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    #sk-container-id-35 div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
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    #sk-container-id-35 div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    #sk-container-id-35 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-container-id-35 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-container-id-35 label.sk-toggleable__label {
      cursor: pointer;
      display: flex;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
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      gap: 0.5em;
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    #sk-container-id-35 label.sk-toggleable__label .caption {
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    #sk-container-id-35 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
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      background-color: var(--sklearn-color-unfitted-level-2);
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      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    #sk-container-id-35 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
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      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    #sk-container-id-35 div.sk-label label.sk-toggleable__label,
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      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

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    #sk-container-id-35 div.sk-label:hover label.sk-toggleable__label {
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      background-color: var(--sklearn-color-unfitted-level-2);
    }

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      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

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      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
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      margin-bottom: 0.5em;
      /* unfitted */
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      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
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    /* on hover */
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      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
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    /* 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-background);
      border-radius: 1em;
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      margin-left: 0.5em;
      text-align: center;
      /* unfitted */
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    a:link.sk-estimator-doc-link.fitted,
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      color: var(--sklearn-color-fitted-level-1);
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      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
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    .sk-estimator-doc-link.fitted:hover,
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      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      color: var(--sklearn-color-background);
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      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
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      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

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      /* fitted */
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    }

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      display: block;
    }

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

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

    #sk-container-id-35 a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }
    </style><div id="sk-container-id-35" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>SVC(random_state=42)</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"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-120" type="checkbox" checked><label for="sk-estimator-id-120" class="sk-toggleable__label fitted sk-toggleable__label-arrow"><div><div>SVC</div></div><div><a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/dev/modules/generated/sklearn.svm.SVC.html">?<span>Documentation for SVC</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></div></label><div class="sk-toggleable__content fitted"><pre>SVC(random_state=42)</pre></div> </div></div></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 32-37

رسم منحنى ROC
----------------------
بعد ذلك، نرسم منحنى ROC باستخدام مكالمة واحدة لـ
:func:`sklearn.metrics.RocCurveDisplay.from_estimator`. الكائن `svc_disp` الذي يتم إرجاعه يسمح لنا بالاستمرار في استخدام منحنى ROC المحسوب بالفعل
لـ SVC في الرسوم البيانية المستقبلية.

.. GENERATED FROM PYTHON SOURCE LINES 37-40

.. code-block:: Python

    svc_disp = RocCurveDisplay.from_estimator(svc, X_test, y_test)
    plt.show()




.. image-sg:: /auto_examples/miscellaneous/images/sphx_glr_plot_roc_curve_visualization_api_001.png
   :alt: plot roc curve visualization api
   :srcset: /auto_examples/miscellaneous/images/sphx_glr_plot_roc_curve_visualization_api_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 41-47

تدريب غابة عشوائية ورسم منحنى ROC
---------------------------------------------------
نقوم بتدريب مصنف الغابة العشوائية وإنشاء رسم بياني يقارنه بمنحنى ROC لـ SVC. لاحظ كيف أن `svc_disp` يستخدم
:func:`~sklearn.metrics.RocCurveDisplay.plot` لرسم منحنى ROC لـ SVC
دون إعادة حساب قيم منحنى ROC نفسه. علاوة على ذلك، نقوم
بتمرير `alpha=0.8` إلى دالات الرسم لتعديل قيم ألفا للمنحنيات.

.. GENERATED FROM PYTHON SOURCE LINES 47-52

.. code-block:: Python

    rfc = RandomForestClassifier(n_estimators=10, random_state=42)
    rfc.fit(X_train, y_train)
    ax = plt.gca()
    rfc_disp = RocCurveDisplay.from_estimator(rfc, X_test, y_test, ax=ax, alpha=0.8)
    svc_disp.plot(ax=ax, alpha=0.8)
    plt.show()


.. image-sg:: /auto_examples/miscellaneous/images/sphx_glr_plot_roc_curve_visualization_api_002.png
   :alt: plot roc curve visualization api
   :srcset: /auto_examples/miscellaneous/images/sphx_glr_plot_roc_curve_visualization_api_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.168 seconds)


.. _sphx_glr_download_auto_examples_miscellaneous_plot_roc_curve_visualization_api.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/miscellaneous/plot_roc_curve_visualization_api.ipynb
        :alt: Launch binder
        :width: 150 px

    .. container:: lite-badge

      .. image:: images/jupyterlite_badge_logo.svg
        :target: ../../lite/lab/index.html?path=auto_examples/miscellaneous/plot_roc_curve_visualization_api.ipynb
        :alt: Launch JupyterLite
        :width: 150 px

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

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

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

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

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

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


.. include:: plot_roc_curve_visualization_api.recommendations


.. only:: html

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

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