.. _example_gaussian_process_plot_gp_regression.py:


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Gaussian Processes regression: basic introductory example
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A simple one-dimensional regression exercise with a cubic correlation
model whose parameters are estimated using the maximum likelihood principle.

The figure illustrates the interpolating property of the Gaussian Process
model as well as its probabilistic nature in the form of a pointwise 95%
confidence interval.


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

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

.. literalinclude:: plot_gp_regression.py
    :lines: 16-