

.. _example_ensemble_plot_gradient_boosting_regularization.py:


================================
Gradient Boosting regularization
================================

Illustration of the effect of different regularization strategies
for Gradient Boosting. The example is taken from Hastie et al 2009.

The loss function used is binomial deviance. In combination with
shrinkage, stochastic gradient boosting (Sample 0.5) can produce
more accurate models.
Subsampling without shrinkage usually does poorly.

.. [1] T. Hastie, R. Tibshirani and J. Friedman, "Elements of Statistical
    Learning Ed. 2", Springer, 2009.



.. image:: images/plot_gradient_boosting_regularization_1.png
    :align: center




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

.. literalinclude:: plot_gradient_boosting_regularization.py
    :lines: 17-
    