.. _sphx_glr_auto_examples_Metrics:

Metrics
====================



.. raw:: html

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

.. thumbnail-parent-div-open

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This script demonstrates the use of ROC Curve for binary classification on synthetic data.  The dataset is generated using make_blobs from scikit-learn to create a 2D feature space with two  centers. The script then splits the dataset into training and test sets, trains a logistic regression  model, and evaluates its performance using metrics such as accuracy, ROC curve, and AUC (Area Under the  Curve).">

.. only:: html

  .. image:: /auto_examples/Metrics/images/thumb/sphx_glr_ROC_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_Metrics_ROC.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Logistic Regression on Synthetic Data with ROC Curve and AUC</div>
    </div>


.. thumbnail-parent-div-close

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_examples/Metrics/ROC