.. _example_svm_plot_rbf_parameters.py:


==================
RBF SVM parameters
==================

This example illustrates the effect of the parameters `gamma`
and `C` of the rbf kernel SVM.

Intuitively, the `gamma` parameter defines how far the influence
of a single training example reaches, with low values meaning 'far'
and high values meaning 'close'.
The `C` parameter trades off misclassification of training examples
against simplicity of the decision surface. A low C makes
the decision surface smooth, while a high C aims at classifying
all training examples correctly.



.. image:: images/plot_rbf_parameters_1.png
    :align: center




**Python source code:** :download:`plot_rbf_parameters.py <plot_rbf_parameters.py>`

.. literalinclude:: plot_rbf_parameters.py
    :lines: 17-