.. _example_ensemble_plot_voting_decision_regions.py:


==================================================
Plot the decision boundaries of a VotingClassifier
==================================================

Plot the decision boundaries of a `VotingClassifier` for
two features of the Iris dataset.

Plot the class probabilities of the first sample in a toy dataset
predicted by three different classifiers and averaged by the
`VotingClassifier`.

First, three examplary classifiers are initialized (`DecisionTreeClassifier`,
`KNeighborsClassifier`, and `SVC`) and used to initialize a
soft-voting `VotingClassifier` with weights `[2, 1, 2]`, which means that
the predicted probabilities of the `DecisionTreeClassifier` and `SVC`
count 5 times as much as the weights of the `KNeighborsClassifier` classifier
when the averaged probability is calculated.




.. image:: images/\plot_voting_decision_regions_001.png
    :align: center




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

.. literalinclude:: plot_voting_decision_regions.py
    :lines: 21-

**Total running time of the example:**  1.29 seconds
( 0 minutes  1.29 seconds)