.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/cluster/plot_kmeans_plusplus.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_cluster_plot_kmeans_plusplus.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_cluster_plot_kmeans_plusplus.py:


===========================================================
An example of K-Means++ initialization
===========================================================

An example to show the output of the :func:`sklearn.cluster.kmeans_plusplus`
function for generating initial seeds for clustering.

K-Means++ is used as the default initialization for :ref:`k_means`.

.. GENERATED FROM PYTHON SOURCE LINES 12-46



.. image:: /auto_examples/cluster/images/sphx_glr_plot_kmeans_plusplus_001.png
    :alt: K-Means++ Initialization
    :class: sphx-glr-single-img





.. code-block:: default

    print(__doc__)

    from sklearn.cluster import kmeans_plusplus
    from sklearn.datasets import make_blobs
    import matplotlib.pyplot as plt

    # Generate sample data
    n_samples = 4000
    n_components = 4

    X, y_true = make_blobs(n_samples=n_samples,
                           centers=n_components,
                           cluster_std=0.60,
                           random_state=0)
    X = X[:, ::-1]

    # Calculate seeds from kmeans++
    centers_init, indices = kmeans_plusplus(X, n_clusters=4,
                                            random_state=0)

    # Plot init seeds along side sample data
    plt.figure(1)
    colors = ['#4EACC5', '#FF9C34', '#4E9A06', 'm']

    for k, col in enumerate(colors):
        cluster_data = y_true == k
        plt.scatter(X[cluster_data, 0], X[cluster_data, 1],
                    c=col, marker='.', s=10)

    plt.scatter(centers_init[:, 0], centers_init[:, 1], c='b', s=50)
    plt.title("K-Means++ Initialization")
    plt.xticks([])
    plt.yticks([])
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.098 seconds)


.. _sphx_glr_download_auto_examples_cluster_plot_kmeans_plusplus.py:


.. only :: html

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


  .. container:: binder-badge

    .. image:: images/binder_badge_logo.svg
      :target: https://mybinder.org/v2/gh/scikit-learn/scikit-learn/0.24.X?urlpath=lab/tree/notebooks/auto_examples/cluster/plot_kmeans_plusplus.ipynb
      :alt: Launch binder
      :width: 150 px


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

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



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

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


.. only:: html

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

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