.. We want the previous/next button to work on the user guide pages and on the
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    tutorial/index
    user_guide
    auto_examples/index
    faq
    support
    whats_new
    presentations
    about
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    datasets/covtype
    datasets/labeled_faces
    datasets/mldata
    datasets/olivetti_faces
    datasets/twenty_newsgroups
    modules/classes
    testimonials/testimonials
    developers/index
    developers/debugging
    developers/maintainer
    developers/performance
    developers/utilities
    install
    tutorial/basic/tutorial
    tutorial/machine_learning_map/index



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.. This is were the real work starts.


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    <!-- Classification -->
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:ref:`Classification <supervised-learning>`

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    </h2>
    <blockquote>
    <p>Identifying to which category an object belongs to.</p>
    <div class="box-links">
    <strong>Applications</strong>: Spam detection, Image recognition.</br>
    <strong>Algorithms</strong>:&nbsp;

:ref:`SVM<svm>`, :ref:`nearest neighbors<classification>`, :ref:`random forest<forest>`, ...

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:ref:`Examples<general_examples>`

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:ref:`Regression <supervised-learning>`

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    <p>Predicting a continuous-valued attribute associated with an object.</p>
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    <strong>Algorithms</strong>:&nbsp;

:ref:`SVR<svm>`, :ref:`ridge regression<ridge_regression>`, :ref:`Lasso<lasso>`, ...

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:ref:`Examples<general_examples>`

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:ref:`Clustering<clustering>`

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    </h2>
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    <p>Automatic grouping of similar objects into sets.</p>
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    <strong>Applications</strong>: Customer segmentation, Grouping experiment outcomes</br>
    <strong>Algorithms</strong>:&nbsp;

:ref:`k-Means<k_means>`, :ref:`spectral clustering<spectral_clustering>`, :ref:`mean-shift<mean_shift>`, ...

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:ref:`Examples<cluster_examples>`

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:ref:`Dimensionality reduction<decompositions>`

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    </h2>
    <blockquote>
    <p>Reducing the number of random variables to consider.</p>
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    <strong>Applications</strong>: Visualization, Increased efficiency</br>
    <strong>Algorithms</strong>:&nbsp;

:ref:`PCA<PCA>`, :ref:`feature selection<feature_selection>`, :ref:`non-negative matrix factorization<NMF>`.

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:ref:`Examples<decomposition_examples>`

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:ref:`Model selection<model_selection>`

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    </h2>
    <blockquote>
    <p>Comparing, validating and choosing parameters and models.</p>
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    <strong>Goal</strong>: Improved accuracy via parameter tuning</br>
    <strong>Modules</strong>:&nbsp;

:ref:`grid search<grid_search>`, :ref:`cross validation<cross_validation>`, :ref:`metrics<model_evaluation>`.

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:ref:`Examples<general_examples>`

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:ref:`Preprocessing<preprocessing>`

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    </h2>
    <blockquote>
    <p>Feature extraction and normalization.</p>
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    <strong>Application</strong>: Transforming input data such as text for use with machine learning algorithms.</br>
    <strong>Modules</strong>:&nbsp;

:ref:`preprocessing<preprocessing>`, :ref:`feature extraction<feature_extraction>`.

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:ref:`Examples<general_examples>`

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