.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/_general/plot_kernel_rim.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__general_plot_kernel_rim.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples__general_plot_kernel_rim.py:


===================================
Clustering circles with kernel RIM
===================================

We show here a simple dataset consisting in two centred circle that can be challenging for some clustering algorithms.
We solve this case using the kernel RIM algorithm. This algorithm fits a logistic regression on the kernel
matrix derived from the dataset.

.. GENERATED FROM PYTHON SOURCE LINES 10-16

.. code-block:: Python

    from matplotlib import pyplot as plt
    from sklearn import datasets
    from sklearn import metrics

    from gemclus.linear import KernelRIM








.. GENERATED FROM PYTHON SOURCE LINES 17-19

Draw samples for the circle dataset
-------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 21-29

.. code-block:: Python


    # We start by generating samples distributed on two circles
    noise = 0.05
    factor = 0.1
    X, y = datasets.make_circles(n_samples=200, noise=noise, factor=factor, random_state=0)
    mean, std = X.mean(0), X.std(0)
    X = (X-mean)/std








.. GENERATED FROM PYTHON SOURCE LINES 30-32

Training clustering model
---------------------------

.. GENERATED FROM PYTHON SOURCE LINES 34-38

.. code-block:: Python

    model_kernel = KernelRIM(n_clusters=2, base_kernel="rbf", reg=0, random_state=0)
    y_pred = model_kernel.fit_predict(X)
    print(f"ARI = {metrics.adjusted_rand_score(y, y_pred)}")





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

 .. code-block:: none

    /home/circleci/.local/lib/python3.10/site-packages/sklearn/base.py:474: FutureWarning: `BaseEstimator._validate_data` is deprecated in 1.6 and will be removed in 1.7. Use `sklearn.utils.validation.validate_data` instead. This function becomes public and is part of the scikit-learn developer API.
      warnings.warn(
    ARI = 1.0




.. GENERATED FROM PYTHON SOURCE LINES 39-41

Show predictions on similar samples
------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 41-53

.. code-block:: Python


    # Create a novel set of samples and cluster them
    new_X, new_y = datasets.make_circles(n_samples=200, noise=noise, factor=factor, random_state=1)
    new_X = (new_X-mean)/std
    new_pred = model_kernel.predict(new_X)
    print(f"ARI = {metrics.adjusted_rand_score(new_y, new_pred)}")


    plt.scatter(X[:, 0], X[:, 1], c=y_pred, marker="+", label="Training samples")
    plt.scatter(new_X[:, 0], new_X[:, 1], c=new_pred, marker="o", label="Testing samples")
    plt.legend()
    plt.show()



.. image-sg:: /auto_examples/_general/images/sphx_glr_plot_kernel_rim_001.png
   :alt: plot kernel rim
   :srcset: /auto_examples/_general/images/sphx_glr_plot_kernel_rim_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    ARI = 1.0





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

   **Total running time of the script:** (0 minutes 0.388 seconds)


.. _sphx_glr_download_auto_examples__general_plot_kernel_rim.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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