.. _example_tree_plot_tree_regression.py:


===================================================================
Decision Tree Regression
===================================================================

1D regression with :ref:`decision trees <tree>`: the decision tree is
used to fit a sine curve with addition noisy observation. As a result, it
learns local linear regressions approximating the sine curve.

We can see that if the maximum depth of the tree (controled by the
`max_depth` parameter) is set too high, the decision trees learn too fine
details of the training data and learn from the noise, i.e. they overfit.



.. image:: images/plot_tree_regression_1.png
    :align: center




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

.. literalinclude:: plot_tree_regression.py
    :lines: 14-