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| .. | ||
| applications | ||
| bicluster | ||
| calibration | ||
| callbacks | ||
| classification | ||
| cluster | ||
| compose | ||
| covariance | ||
| cross_decomposition | ||
| datasets | ||
| decomposition | ||
| developing_estimators | ||
| ensemble | ||
| feature_selection | ||
| frozen | ||
| gaussian_process | ||
| impute | ||
| inspection | ||
| kernel_approximation | ||
| linear_model | ||
| manifold | ||
| miscellaneous | ||
| mixture | ||
| model_selection | ||
| multiclass | ||
| multioutput | ||
| neighbors | ||
| neural_networks | ||
| preprocessing | ||
| release_highlights | ||
| semi_supervised | ||
| svm | ||
| text | ||
| tree | ||
| README.txt | ||
README.txt
.. _general_examples: Examples ======== This is the gallery of examples that showcase how scikit-learn can be used. Some examples demonstrate the use of the :ref:`API <api_ref>` in general and some demonstrate specific applications in tutorial form. Also check out our :ref:`user guide <user_guide>` for more detailed illustrations.