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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_svm_plot_svm_kernels.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_svm_plot_svm_kernels.py:


=========================================================
SVM-Kernels
=========================================================

Three different types of SVM-Kernels are displayed below.
The polynomial and RBF are especially useful when the
data-points are not linearly separable.

.. GENERATED FROM PYTHON SOURCE LINES 13-95



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/svm/images/sphx_glr_plot_svm_kernels_001.png
         :alt: plot svm kernels
         :srcset: /auto_examples/svm/images/sphx_glr_plot_svm_kernels_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/svm/images/sphx_glr_plot_svm_kernels_002.png
         :alt: plot svm kernels
         :srcset: /auto_examples/svm/images/sphx_glr_plot_svm_kernels_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/svm/images/sphx_glr_plot_svm_kernels_003.png
         :alt: plot svm kernels
         :srcset: /auto_examples/svm/images/sphx_glr_plot_svm_kernels_003.png
         :class: sphx-glr-multi-img





.. code-block:: default


    # Code source: Gaël Varoquaux
    # License: BSD 3 clause

    import numpy as np
    import matplotlib.pyplot as plt
    from sklearn import svm


    # Our dataset and targets
    X = np.c_[
        (0.4, -0.7),
        (-1.5, -1),
        (-1.4, -0.9),
        (-1.3, -1.2),
        (-1.1, -0.2),
        (-1.2, -0.4),
        (-0.5, 1.2),
        (-1.5, 2.1),
        (1, 1),
        # --
        (1.3, 0.8),
        (1.2, 0.5),
        (0.2, -2),
        (0.5, -2.4),
        (0.2, -2.3),
        (0, -2.7),
        (1.3, 2.1),
    ].T
    Y = [0] * 8 + [1] * 8

    # figure number
    fignum = 1

    # fit the model
    for kernel in ("linear", "poly", "rbf"):
        clf = svm.SVC(kernel=kernel, gamma=2)
        clf.fit(X, Y)

        # plot the line, the points, and the nearest vectors to the plane
        plt.figure(fignum, figsize=(4, 3))
        plt.clf()

        plt.scatter(
            clf.support_vectors_[:, 0],
            clf.support_vectors_[:, 1],
            s=80,
            facecolors="none",
            zorder=10,
            edgecolors="k",
        )
        plt.scatter(X[:, 0], X[:, 1], c=Y, zorder=10, cmap=plt.cm.Paired, edgecolors="k")

        plt.axis("tight")
        x_min = -3
        x_max = 3
        y_min = -3
        y_max = 3

        XX, YY = np.mgrid[x_min:x_max:200j, y_min:y_max:200j]
        Z = clf.decision_function(np.c_[XX.ravel(), YY.ravel()])

        # Put the result into a color plot
        Z = Z.reshape(XX.shape)
        plt.figure(fignum, figsize=(4, 3))
        plt.pcolormesh(XX, YY, Z > 0, cmap=plt.cm.Paired)
        plt.contour(
            XX,
            YY,
            Z,
            colors=["k", "k", "k"],
            linestyles=["--", "-", "--"],
            levels=[-0.5, 0, 0.5],
        )

        plt.xlim(x_min, x_max)
        plt.ylim(y_min, y_max)

        plt.xticks(())
        plt.yticks(())
        fignum = fignum + 1
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.186 seconds)


.. _sphx_glr_download_auto_examples_svm_plot_svm_kernels.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/1.0.X?urlpath=lab/tree/notebooks/auto_examples/svm/plot_svm_kernels.ipynb
      :alt: Launch binder
      :width: 150 px


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

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



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

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


.. only:: html

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

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