.. _sphx_glr_auto_examples_feature_selection_plot_feature_selection_pipeline.py:


==================
Pipeline Anova SVM
==================

Simple usage of Pipeline that runs successively a univariate
feature selection with anova and then a C-SVM of the selected features.





.. rst-class:: sphx-glr-script-out

 Out::

    precision    recall  f1-score   support

              0       1.00      0.88      0.93         8
              1       1.00      0.83      0.91         6
              2       0.57      0.67      0.62         6
              3       0.67      0.80      0.73         5

    avg / total       0.83      0.80      0.81        25




|


.. code-block:: python

    from sklearn import svm
    from sklearn.datasets import samples_generator
    from sklearn.feature_selection import SelectKBest, f_regression
    from sklearn.pipeline import make_pipeline
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import classification_report

    print(__doc__)

    # import some data to play with
    X, y = samples_generator.make_classification(
        n_features=20, n_informative=3, n_redundant=0, n_classes=4,
        n_clusters_per_class=2)

    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)

    # ANOVA SVM-C
    # 1) anova filter, take 3 best ranked features
    anova_filter = SelectKBest(f_regression, k=3)
    # 2) svm
    clf = svm.SVC(kernel='linear')

    anova_svm = make_pipeline(anova_filter, clf)
    anova_svm.fit(X_train, y_train)
    y_pred = anova_svm.predict(X_test)
    print(classification_report(y_test, y_pred))

**Total running time of the script:** ( 0 minutes  0.004 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_feature_selection_pipeline.py <plot_feature_selection_pipeline.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_feature_selection_pipeline.ipynb <plot_feature_selection_pipeline.ipynb>`

.. rst-class:: sphx-glr-signature

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