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

    Click :ref:`here <sphx_glr_download_auto_examples_plot_compare_rvr_svr.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_compare_rvr_svr.py:


=====================================================================
Comparison of relevance vector machine and support vector machine
=====================================================================



.. image:: /auto_examples/images/sphx_glr_plot_compare_rvr_svr_001.png
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none


    Time for SVR fitting: 0.001
    /home/docs/checkouts/readthedocs.org/user_builds/sklearn-rvm/envs/latest/lib/python3.7/site-packages/sklearn_rvm/em_rvm.py:271: FutureWarning: The default value of gamma will change from 'auto' to 'scale' in version 0.22 to account better for unscaled features. Set gamma explicitly to 'auto' or 'scale' to avoid this warning.
      "avoid this warning.", FutureWarning)
    Time for RVR fitting: 1.196
    Time for SVR prediction: 0.008
    Time for RVR prediction: 0.010
    Time for RVR prediction with standard-deviation: 7.673






|


.. code-block:: default

    print(__doc__)

    import time

    import matplotlib.pyplot as plt
    import numpy as np
    from sklearn.svm import SVR
    from sklearn_rvm import EMRVR

    np.random.seed(8)
    rng = np.random.RandomState(0)

    # Generate sample data
    X = 4 * np.pi * np.random.random(100) - 2 * np.pi
    y = np.sinc(X)
    y += 0.25 * (0.5 - rng.rand(X.shape[0]))  # add noise

    X = X[:, None]

    # Fit SVR
    svr = SVR(kernel="rbf", gamma="auto")
    stime = time.time()
    svr.fit(X, y)
    print("Time for SVR fitting: %.3f" % (time.time() - stime))

    # Fit RVR
    rvr = EMRVR(kernel="rbf")
    stime = time.time()
    rvr.fit(X, y)
    print("Time for RVR fitting: %.3f" % (time.time() - stime))

    X_plot = np.linspace(-2 * np.pi, 2 * np.pi, 10000)[:, None]
    # Predict using SVR
    stime = time.time()
    y_svr = svr.predict(X_plot)
    print("Time for SVR prediction: %.3f" % (time.time() - stime))

    # Predict using Rvm
    stime = time.time()
    y_rvr = rvr.predict(X_plot, return_std=False)
    print("Time for RVR prediction: %.3f" % (time.time() - stime))

    stime = time.time()
    y_rvr, y_std = rvr.predict(X_plot, return_std=True)
    print("Time for RVR prediction with standard-deviation: %.3f" % (time.time() - stime))

    # Plot results
    fig = plt.figure(figsize=(10, 5))
    lw = 2
    fig.suptitle("RVR versus SVR", fontsize=16)

    plt.subplot(121)
    plt.scatter(X, y, marker=".", c="k", label="data")
    plt.plot(X_plot, np.sinc(X_plot), color="navy", lw=lw, label="True")

    plt.plot(X_plot, y_svr, color="turquoise", lw=lw, label="SVR")
    support_vectors_idx = svr.support_
    plt.scatter(X[support_vectors_idx], y[support_vectors_idx], s=80, facecolors="none", edgecolors="r",
                label="support vectors")
    plt.ylabel("target")
    plt.xlabel("data")
    plt.legend(loc="best", scatterpoints=1, prop={"size": 8})

    plt.subplot(122)
    plt.scatter(X, y, marker=".", c="k", label="data")
    plt.plot(X_plot, np.sinc(X_plot), color="navy", lw=lw, label="True")

    plt.plot(X_plot, y_rvr, color="darkorange", lw=lw, label="RVR")
    plt.fill_between(X_plot[:, 0], y_rvr - y_std, y_rvr + y_std, color="darkorange", alpha=0.2)
    relevance_vectors_idx = rvr.relevance_
    plt.scatter(X[relevance_vectors_idx], y[relevance_vectors_idx], s=80, facecolors="none", edgecolors="r",
                label="relevance vectors")

    plt.xlabel("data")
    plt.legend(loc="best", scatterpoints=1, prop={"size": 8})
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  9.225 seconds)


.. _sphx_glr_download_auto_examples_plot_compare_rvr_svr.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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