.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/svm/plot_svm_regression.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_svm_plot_svm_regression.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_regression.py:


===================================================================
使用线性和非线性核的支持向量回归 (SVR)
===================================================================

使用线性、多项式和RBF核的一维回归玩具示例。

.. GENERATED FROM PYTHON SOURCE LINES 9-15

.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    from sklearn.svm import SVR








.. GENERATED FROM PYTHON SOURCE LINES 16-18

生成示例数据
--------------------

.. GENERATED FROM PYTHON SOURCE LINES 18-25

.. code-block:: Python


    X = np.sort(5 * np.random.rand(40, 1), axis=0)
    y = np.sin(X).ravel()

    # 添加噪声到目标
    y[::5] += 3 * (0.5 - np.random.rand(8))








.. GENERATED FROM PYTHON SOURCE LINES 26-28

拟合回归模型
--------------------

.. GENERATED FROM PYTHON SOURCE LINES 28-33

.. code-block:: Python


    svr_rbf = SVR(kernel="rbf", C=100, gamma=0.1, epsilon=0.1)
    svr_lin = SVR(kernel="linear", C=100, gamma="auto")
    svr_poly = SVR(kernel="poly", C=100, gamma="auto", degree=3, epsilon=0.1, coef0=1)








.. GENERATED FROM PYTHON SOURCE LINES 34-36

查看结果
-------------------

.. GENERATED FROM PYTHON SOURCE LINES 36-80

.. code-block:: Python


    lw = 2

    svrs = [svr_rbf, svr_lin, svr_poly]
    kernel_label = ["RBF", "Linear", "Polynomial"]
    model_color = ["m", "c", "g"]

    fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(15, 10), sharey=True)
    for ix, svr in enumerate(svrs):
        axes[ix].plot(
            X,
            svr.fit(X, y).predict(X),
            color=model_color[ix],
            lw=lw,
            label="{} model".format(kernel_label[ix]),
        )
        axes[ix].scatter(
            X[svr.support_],
            y[svr.support_],
            facecolor="none",
            edgecolor=model_color[ix],
            s=50,
            label="{} support vectors".format(kernel_label[ix]),
        )
        axes[ix].scatter(
            X[np.setdiff1d(np.arange(len(X)), svr.support_)],
            y[np.setdiff1d(np.arange(len(X)), svr.support_)],
            facecolor="none",
            edgecolor="k",
            s=50,
            label="other training data",
        )
        axes[ix].legend(
            loc="upper center",
            bbox_to_anchor=(0.5, 1.1),
            ncol=1,
            fancybox=True,
            shadow=True,
        )

    fig.text(0.5, 0.04, "data", ha="center", va="center")
    fig.text(0.06, 0.5, "target", ha="center", va="center", rotation="vertical")
    fig.suptitle("Support Vector Regression", fontsize=14)
    plt.show()



.. image-sg:: /auto_examples/svm/images/sphx_glr_plot_svm_regression_001.png
   :alt: Support Vector Regression
   :srcset: /auto_examples/svm/images/sphx_glr_plot_svm_regression_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.347 seconds)


.. _sphx_glr_download_auto_examples_svm_plot_svm_regression.py:

.. only:: html

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

    .. container:: binder-badge

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

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

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

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

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

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

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


.. include:: plot_svm_regression.recommendations


.. only:: html

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

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