.. _sphx_glr_auto_examples_ensemble: .. _ensemble_examples: Example using ensemble class methods ==================================== Under-sampling methods implies that samples of the majority class are lost during the balancing procedure. Ensemble methods offer an alternative to use most of the samples. In fact, an ensemble of balanced sets is created and used to later train any classifier. .. raw:: html
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.. only:: html .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_bagging_classifier_thumb.png :alt: :ref:`sphx_glr_auto_examples_ensemble_plot_bagging_classifier.py` .. raw:: html
Bagging classifiers using sampler
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.. only:: html .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_comparison_ensemble_classifier_thumb.png :alt: :ref:`sphx_glr_auto_examples_ensemble_plot_comparison_ensemble_classifier.py` .. raw:: html
Compare ensemble classifiers using resampling
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.. toctree:: :hidden: /auto_examples/ensemble/plot_bagging_classifier /auto_examples/ensemble/plot_comparison_ensemble_classifier