.. _sphx_glr_auto_examples_Calibration:

Probability Calibration
=============================



.. raw:: html

    <div class="sphx-glr-thumbnails">

.. thumbnail-parent-div-open

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This script showcases the use of IsotonicRegression for predicting monotonic relationships.">

.. only:: html

  .. image:: /auto_examples/Calibration/images/thumb/sphx_glr_IsotonicRegression_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_Calibration_IsotonicRegression.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Isotonic regression</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This script evaluates the calibration of multiple classification models using different calibration methods. It generates calibration curves for logistic regression, Gaussian Naive Bayes, and support vector classification (SVC), with and without calibration, and visualizes the results in a series of plots.">

.. only:: html

  .. image:: /auto_examples/Calibration/images/thumb/sphx_glr_Calibration_curve_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_Calibration_Calibration_curve.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Calibration of Classification Models</div>
    </div>


.. thumbnail-parent-div-close

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_examples/Calibration/IsotonicRegression
   /auto_examples/Calibration/Calibration_curve