index.rst.txt

orphan:

Examples

Release Highlights

These examples illustrate the main features of the releases of scikit-learn.

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  .. image:: /auto_examples/release_highlights/images/thumb/sphx_glr_plot_release_highlights_1_1_0_thumb.png
    :alt: Release Highlights for scikit-learn 1.1

  :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_1_0.py`

Release Highlights for scikit-learn 1.1

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  .. image:: /auto_examples/release_highlights/images/thumb/sphx_glr_plot_release_highlights_1_0_0_thumb.png
    :alt: Release Highlights for scikit-learn 1.0

  :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_0_0.py`

Release Highlights for scikit-learn 1.0

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  .. image:: /auto_examples/release_highlights/images/thumb/sphx_glr_plot_release_highlights_0_24_0_thumb.png
    :alt: Release Highlights for scikit-learn 0.24

  :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_0_24_0.py`

Release Highlights for scikit-learn 0.24

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  .. image:: /auto_examples/release_highlights/images/thumb/sphx_glr_plot_release_highlights_0_23_0_thumb.png
    :alt: Release Highlights for scikit-learn 0.23

  :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_0_23_0.py`

Release Highlights for scikit-learn 0.23

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  .. image:: /auto_examples/release_highlights/images/thumb/sphx_glr_plot_release_highlights_0_22_0_thumb.png
    :alt: Release Highlights for scikit-learn 0.22

  :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_0_22_0.py`

Release Highlights for scikit-learn 0.22

Biclustering

Examples concerning the :mod:`sklearn.cluster.bicluster` module.

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  .. image:: /auto_examples/bicluster/images/thumb/sphx_glr_plot_spectral_biclustering_thumb.png
    :alt: A demo of the Spectral Biclustering algorithm

  :ref:`sphx_glr_auto_examples_bicluster_plot_spectral_biclustering.py`

A demo of the Spectral Biclustering algorithm

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  .. image:: /auto_examples/bicluster/images/thumb/sphx_glr_plot_spectral_coclustering_thumb.png
    :alt: A demo of the Spectral Co-Clustering algorithm

  :ref:`sphx_glr_auto_examples_bicluster_plot_spectral_coclustering.py`

A demo of the Spectral Co-Clustering algorithm

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  .. image:: /auto_examples/bicluster/images/thumb/sphx_glr_plot_bicluster_newsgroups_thumb.png
    :alt: Biclustering documents with the Spectral Co-clustering algorithm

  :ref:`sphx_glr_auto_examples_bicluster_plot_bicluster_newsgroups.py`

Biclustering documents with the Spectral Co-clustering algorithm

Calibration

Examples illustrating the calibration of predicted probabilities of classifiers.

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  .. image:: /auto_examples/calibration/images/thumb/sphx_glr_plot_compare_calibration_thumb.png
    :alt: Comparison of Calibration of Classifiers

  :ref:`sphx_glr_auto_examples_calibration_plot_compare_calibration.py`

Comparison of Calibration of Classifiers

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  .. image:: /auto_examples/calibration/images/thumb/sphx_glr_plot_calibration_curve_thumb.png
    :alt: Probability Calibration curves

  :ref:`sphx_glr_auto_examples_calibration_plot_calibration_curve.py`

Probability Calibration curves

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  .. image:: /auto_examples/calibration/images/thumb/sphx_glr_plot_calibration_multiclass_thumb.png
    :alt: Probability Calibration for 3-class classification

  :ref:`sphx_glr_auto_examples_calibration_plot_calibration_multiclass.py`

Probability Calibration for 3-class classification

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  .. image:: /auto_examples/calibration/images/thumb/sphx_glr_plot_calibration_thumb.png
    :alt: Probability calibration of classifiers

  :ref:`sphx_glr_auto_examples_calibration_plot_calibration.py`

Probability calibration of classifiers

Classification

General examples about classification algorithms.

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  .. image:: /auto_examples/classification/images/thumb/sphx_glr_plot_classifier_comparison_thumb.png
    :alt: Classifier comparison

  :ref:`sphx_glr_auto_examples_classification_plot_classifier_comparison.py`

Classifier comparison

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  .. image:: /auto_examples/classification/images/thumb/sphx_glr_plot_lda_qda_thumb.png
    :alt: Linear and Quadratic Discriminant Analysis with covariance ellipsoid

  :ref:`sphx_glr_auto_examples_classification_plot_lda_qda.py`

Linear and Quadratic Discriminant Analysis with covariance ellipsoid

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  .. image:: /auto_examples/classification/images/thumb/sphx_glr_plot_lda_thumb.png
    :alt: Normal, Ledoit-Wolf and OAS Linear Discriminant Analysis for classification

  :ref:`sphx_glr_auto_examples_classification_plot_lda.py`

Normal, Ledoit-Wolf and OAS Linear Discriminant Analysis for classification

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  .. image:: /auto_examples/classification/images/thumb/sphx_glr_plot_classification_probability_thumb.png
    :alt: Plot classification probability

  :ref:`sphx_glr_auto_examples_classification_plot_classification_probability.py`

Plot classification probability

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  .. image:: /auto_examples/classification/images/thumb/sphx_glr_plot_digits_classification_thumb.png
    :alt: Recognizing hand-written digits

  :ref:`sphx_glr_auto_examples_classification_plot_digits_classification.py`

Recognizing hand-written digits

Clustering

Examples concerning the :mod:`sklearn.cluster` module.

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_kmeans_digits_thumb.png
    :alt: A demo of K-Means clustering on the handwritten digits data

  :ref:`sphx_glr_auto_examples_cluster_plot_kmeans_digits.py`

A demo of K-Means clustering on the handwritten digits data

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_coin_ward_segmentation_thumb.png
    :alt: A demo of structured Ward hierarchical clustering on an image of coins

  :ref:`sphx_glr_auto_examples_cluster_plot_coin_ward_segmentation.py`

A demo of structured Ward hierarchical clustering on an image of coins

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_mean_shift_thumb.png
    :alt: A demo of the mean-shift clustering algorithm

  :ref:`sphx_glr_auto_examples_cluster_plot_mean_shift.py`

A demo of the mean-shift clustering algorithm

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_adjusted_for_chance_measures_thumb.png
    :alt: Adjustment for chance in clustering performance evaluation

  :ref:`sphx_glr_auto_examples_cluster_plot_adjusted_for_chance_measures.py`

Adjustment for chance in clustering performance evaluation

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_agglomerative_clustering_thumb.png
    :alt: Agglomerative clustering with and without structure

  :ref:`sphx_glr_auto_examples_cluster_plot_agglomerative_clustering.py`

Agglomerative clustering with and without structure

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_agglomerative_clustering_metrics_thumb.png
    :alt: Agglomerative clustering with different metrics

  :ref:`sphx_glr_auto_examples_cluster_plot_agglomerative_clustering_metrics.py`

Agglomerative clustering with different metrics

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_kmeans_plusplus_thumb.png
    :alt: An example of K-Means++ initialization

  :ref:`sphx_glr_auto_examples_cluster_plot_kmeans_plusplus.py`

An example of K-Means++ initialization

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_bisect_kmeans_thumb.png
    :alt: Bisecting K-Means and Regular K-Means Performance Comparison

  :ref:`sphx_glr_auto_examples_cluster_plot_bisect_kmeans.py`

Bisecting K-Means and Regular K-Means Performance Comparison

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_color_quantization_thumb.png
    :alt: Color Quantization using K-Means

  :ref:`sphx_glr_auto_examples_cluster_plot_color_quantization.py`

Color Quantization using K-Means

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_birch_vs_minibatchkmeans_thumb.png
    :alt: Compare BIRCH and MiniBatchKMeans

  :ref:`sphx_glr_auto_examples_cluster_plot_birch_vs_minibatchkmeans.py`

Compare BIRCH and MiniBatchKMeans

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_cluster_comparison_thumb.png
    :alt: Comparing different clustering algorithms on toy datasets

  :ref:`sphx_glr_auto_examples_cluster_plot_cluster_comparison.py`

Comparing different clustering algorithms on toy datasets

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_linkage_comparison_thumb.png
    :alt: Comparing different hierarchical linkage methods on toy datasets

  :ref:`sphx_glr_auto_examples_cluster_plot_linkage_comparison.py`

Comparing different hierarchical linkage methods on toy datasets

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_mini_batch_kmeans_thumb.png
    :alt: Comparison of the K-Means and MiniBatchKMeans clustering algorithms

  :ref:`sphx_glr_auto_examples_cluster_plot_mini_batch_kmeans.py`

Comparison of the K-Means and MiniBatchKMeans clustering algorithms

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_dbscan_thumb.png
    :alt: Demo of DBSCAN clustering algorithm

  :ref:`sphx_glr_auto_examples_cluster_plot_dbscan.py`

Demo of DBSCAN clustering algorithm

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_optics_thumb.png
    :alt: Demo of OPTICS clustering algorithm

  :ref:`sphx_glr_auto_examples_cluster_plot_optics.py`

Demo of OPTICS clustering algorithm

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_affinity_propagation_thumb.png
    :alt: Demo of affinity propagation clustering algorithm

  :ref:`sphx_glr_auto_examples_cluster_plot_affinity_propagation.py`

Demo of affinity propagation clustering algorithm

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_kmeans_assumptions_thumb.png
    :alt: Demonstration of k-means assumptions

  :ref:`sphx_glr_auto_examples_cluster_plot_kmeans_assumptions.py`

Demonstration of k-means assumptions

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_kmeans_stability_low_dim_dense_thumb.png
    :alt: Empirical evaluation of the impact of k-means initialization

  :ref:`sphx_glr_auto_examples_cluster_plot_kmeans_stability_low_dim_dense.py`

Empirical evaluation of the impact of k-means initialization

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_digits_agglomeration_thumb.png
    :alt: Feature agglomeration

  :ref:`sphx_glr_auto_examples_cluster_plot_digits_agglomeration.py`

Feature agglomeration

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_feature_agglomeration_vs_univariate_selection_thumb.png
    :alt: Feature agglomeration vs. univariate selection

  :ref:`sphx_glr_auto_examples_cluster_plot_feature_agglomeration_vs_univariate_selection.py`

Feature agglomeration vs. univariate selection

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_ward_structured_vs_unstructured_thumb.png
    :alt: Hierarchical clustering: structured vs unstructured ward

  :ref:`sphx_glr_auto_examples_cluster_plot_ward_structured_vs_unstructured.py`

Hierarchical clustering: structured vs unstructured ward

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_inductive_clustering_thumb.png
    :alt: Inductive Clustering

  :ref:`sphx_glr_auto_examples_cluster_plot_inductive_clustering.py`

Inductive Clustering

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_cluster_iris_thumb.png
    :alt: K-means Clustering

  :ref:`sphx_glr_auto_examples_cluster_plot_cluster_iris.py`

K-means Clustering

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_dict_face_patches_thumb.png
    :alt: Online learning of a dictionary of parts of faces

  :ref:`sphx_glr_auto_examples_cluster_plot_dict_face_patches.py`

Online learning of a dictionary of parts of faces

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_agglomerative_dendrogram_thumb.png
    :alt: Plot Hierarchical Clustering Dendrogram

  :ref:`sphx_glr_auto_examples_cluster_plot_agglomerative_dendrogram.py`

Plot Hierarchical Clustering Dendrogram

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_coin_segmentation_thumb.png
    :alt: Segmenting the picture of greek coins in regions

  :ref:`sphx_glr_auto_examples_cluster_plot_coin_segmentation.py`

Segmenting the picture of greek coins in regions

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_kmeans_silhouette_analysis_thumb.png
    :alt: Selecting the number of clusters with silhouette analysis on KMeans clustering

  :ref:`sphx_glr_auto_examples_cluster_plot_kmeans_silhouette_analysis.py`

Selecting the number of clusters with silhouette analysis on KMeans clustering

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_segmentation_toy_thumb.png
    :alt: Spectral clustering for image segmentation

  :ref:`sphx_glr_auto_examples_cluster_plot_segmentation_toy.py`

Spectral clustering for image segmentation

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_digits_linkage_thumb.png
    :alt: Various Agglomerative Clustering on a 2D embedding of digits

  :ref:`sphx_glr_auto_examples_cluster_plot_digits_linkage.py`

Various Agglomerative Clustering on a 2D embedding of digits

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  .. image:: /auto_examples/cluster/images/thumb/sphx_glr_plot_face_compress_thumb.png
    :alt: Vector Quantization Example

  :ref:`sphx_glr_auto_examples_cluster_plot_face_compress.py`

Vector Quantization Example

Covariance estimation

Examples concerning the :mod:`sklearn.covariance` module.

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  .. image:: /auto_examples/covariance/images/thumb/sphx_glr_plot_lw_vs_oas_thumb.png
    :alt: Ledoit-Wolf vs OAS estimation

  :ref:`sphx_glr_auto_examples_covariance_plot_lw_vs_oas.py`

Ledoit-Wolf vs OAS estimation

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  .. image:: /auto_examples/covariance/images/thumb/sphx_glr_plot_mahalanobis_distances_thumb.png
    :alt: Robust covariance estimation and Mahalanobis distances relevance

  :ref:`sphx_glr_auto_examples_covariance_plot_mahalanobis_distances.py`

Robust covariance estimation and Mahalanobis distances relevance

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  .. image:: /auto_examples/covariance/images/thumb/sphx_glr_plot_robust_vs_empirical_covariance_thumb.png
    :alt: Robust vs Empirical covariance estimate

  :ref:`sphx_glr_auto_examples_covariance_plot_robust_vs_empirical_covariance.py`

Robust vs Empirical covariance estimate

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  .. image:: /auto_examples/covariance/images/thumb/sphx_glr_plot_covariance_estimation_thumb.png
    :alt: Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood

  :ref:`sphx_glr_auto_examples_covariance_plot_covariance_estimation.py`

Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood

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  .. image:: /auto_examples/covariance/images/thumb/sphx_glr_plot_sparse_cov_thumb.png
    :alt: Sparse inverse covariance estimation

  :ref:`sphx_glr_auto_examples_covariance_plot_sparse_cov.py`

Sparse inverse covariance estimation

Cross decomposition

Examples concerning the :mod:`sklearn.cross_decomposition` module.

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  .. image:: /auto_examples/cross_decomposition/images/thumb/sphx_glr_plot_compare_cross_decomposition_thumb.png
    :alt: Compare cross decomposition methods

  :ref:`sphx_glr_auto_examples_cross_decomposition_plot_compare_cross_decomposition.py`

Compare cross decomposition methods

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  .. image:: /auto_examples/cross_decomposition/images/thumb/sphx_glr_plot_pcr_vs_pls_thumb.png
    :alt: Principal Component Regression vs Partial Least Squares Regression

  :ref:`sphx_glr_auto_examples_cross_decomposition_plot_pcr_vs_pls.py`

Principal Component Regression vs Partial Least Squares Regression

Dataset examples

Examples concerning the :mod:`sklearn.datasets` module.

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  .. image:: /auto_examples/datasets/images/thumb/sphx_glr_plot_random_dataset_thumb.png
    :alt: Plot randomly generated classification dataset

  :ref:`sphx_glr_auto_examples_datasets_plot_random_dataset.py`

Plot randomly generated classification dataset

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  .. image:: /auto_examples/datasets/images/thumb/sphx_glr_plot_random_multilabel_dataset_thumb.png
    :alt: Plot randomly generated multilabel dataset

  :ref:`sphx_glr_auto_examples_datasets_plot_random_multilabel_dataset.py`

Plot randomly generated multilabel dataset

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  .. image:: /auto_examples/datasets/images/thumb/sphx_glr_plot_digits_last_image_thumb.png
    :alt: The Digit Dataset

  :ref:`sphx_glr_auto_examples_datasets_plot_digits_last_image.py`

The Digit Dataset

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  .. image:: /auto_examples/datasets/images/thumb/sphx_glr_plot_iris_dataset_thumb.png
    :alt: The Iris Dataset

  :ref:`sphx_glr_auto_examples_datasets_plot_iris_dataset.py`

The Iris Dataset

Decision Trees

Examples concerning the :mod:`sklearn.tree` module.

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  .. image:: /auto_examples/tree/images/thumb/sphx_glr_plot_tree_regression_thumb.png
    :alt: Decision Tree Regression

  :ref:`sphx_glr_auto_examples_tree_plot_tree_regression.py`

Decision Tree Regression

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  .. image:: /auto_examples/tree/images/thumb/sphx_glr_plot_tree_regression_multioutput_thumb.png
    :alt: Multi-output Decision Tree Regression

  :ref:`sphx_glr_auto_examples_tree_plot_tree_regression_multioutput.py`

Multi-output Decision Tree Regression

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  .. image:: /auto_examples/tree/images/thumb/sphx_glr_plot_iris_dtc_thumb.png
    :alt: Plot the decision surface of decision trees trained on the iris dataset

  :ref:`sphx_glr_auto_examples_tree_plot_iris_dtc.py`

Plot the decision surface of decision trees trained on the iris dataset

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  .. image:: /auto_examples/tree/images/thumb/sphx_glr_plot_cost_complexity_pruning_thumb.png
    :alt: Post pruning decision trees with cost complexity pruning

  :ref:`sphx_glr_auto_examples_tree_plot_cost_complexity_pruning.py`

Post pruning decision trees with cost complexity pruning

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  .. image:: /auto_examples/tree/images/thumb/sphx_glr_plot_unveil_tree_structure_thumb.png
    :alt: Understanding the decision tree structure

  :ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py`

Understanding the decision tree structure

Decomposition

Examples concerning the :mod:`sklearn.decomposition` module.

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_beta_divergence_thumb.png
    :alt: Beta-divergence loss functions

  :ref:`sphx_glr_auto_examples_decomposition_plot_beta_divergence.py`

Beta-divergence loss functions

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_ica_blind_source_separation_thumb.png
    :alt: Blind source separation using FastICA

  :ref:`sphx_glr_auto_examples_decomposition_plot_ica_blind_source_separation.py`

Blind source separation using FastICA

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_vs_lda_thumb.png
    :alt: Comparison of LDA and PCA 2D projection of Iris dataset

  :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_lda.py`

Comparison of LDA and PCA 2D projection of Iris dataset

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_faces_decomposition_thumb.png
    :alt: Faces dataset decompositions

  :ref:`sphx_glr_auto_examples_decomposition_plot_faces_decomposition.py`

Faces dataset decompositions

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_varimax_fa_thumb.png
    :alt: Factor Analysis (with rotation) to visualize patterns

  :ref:`sphx_glr_auto_examples_decomposition_plot_varimax_fa.py`

Factor Analysis (with rotation) to visualize patterns

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_ica_vs_pca_thumb.png
    :alt: FastICA on 2D point clouds

  :ref:`sphx_glr_auto_examples_decomposition_plot_ica_vs_pca.py`

FastICA on 2D point clouds

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_image_denoising_thumb.png
    :alt: Image denoising using dictionary learning

  :ref:`sphx_glr_auto_examples_decomposition_plot_image_denoising.py`

Image denoising using dictionary learning

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_incremental_pca_thumb.png
    :alt: Incremental PCA

  :ref:`sphx_glr_auto_examples_decomposition_plot_incremental_pca.py`

Incremental PCA

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_kernel_pca_thumb.png
    :alt: Kernel PCA

  :ref:`sphx_glr_auto_examples_decomposition_plot_kernel_pca.py`

Kernel PCA

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_vs_fa_model_selection_thumb.png
    :alt: Model selection with Probabilistic PCA and Factor Analysis (FA)

  :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_fa_model_selection.py`

Model selection with Probabilistic PCA and Factor Analysis (FA)

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_iris_thumb.png
    :alt: PCA example with Iris Data-set

  :ref:`sphx_glr_auto_examples_decomposition_plot_pca_iris.py`

PCA example with Iris Data-set

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_3d_thumb.png
    :alt: Principal components analysis (PCA)

  :ref:`sphx_glr_auto_examples_decomposition_plot_pca_3d.py`

Principal components analysis (PCA)

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_sparse_coding_thumb.png
    :alt: Sparse coding with a precomputed dictionary

  :ref:`sphx_glr_auto_examples_decomposition_plot_sparse_coding.py`

Sparse coding with a precomputed dictionary

Ensemble methods

Examples concerning the :mod:`sklearn.ensemble` module.

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_gradient_boosting_categorical_thumb.png
    :alt: Categorical Feature Support in Gradient Boosting

  :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_categorical.py`

Categorical Feature Support in Gradient Boosting

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_stack_predictors_thumb.png
    :alt: Combine predictors using stacking

  :ref:`sphx_glr_auto_examples_ensemble_plot_stack_predictors.py`

Combine predictors using stacking

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_random_forest_regression_multioutput_thumb.png
    :alt: Comparing random forests and the multi-output meta estimator

  :ref:`sphx_glr_auto_examples_ensemble_plot_random_forest_regression_multioutput.py`

Comparing random forests and the multi-output meta estimator

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_adaboost_regression_thumb.png
    :alt: Decision Tree Regression with AdaBoost

  :ref:`sphx_glr_auto_examples_ensemble_plot_adaboost_regression.py`

Decision Tree Regression with AdaBoost

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_adaboost_hastie_10_2_thumb.png
    :alt: Discrete versus Real AdaBoost

  :ref:`sphx_glr_auto_examples_ensemble_plot_adaboost_hastie_10_2.py`

Discrete versus Real AdaBoost

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_gradient_boosting_early_stopping_thumb.png
    :alt: Early stopping of Gradient Boosting

  :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_early_stopping.py`

Early stopping of Gradient Boosting

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_forest_importances_thumb.png
    :alt: Feature importances with a forest of trees

  :ref:`sphx_glr_auto_examples_ensemble_plot_forest_importances.py`

Feature importances with a forest of trees

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_feature_transformation_thumb.png
    :alt: Feature transformations with ensembles of trees

  :ref:`sphx_glr_auto_examples_ensemble_plot_feature_transformation.py`

Feature transformations with ensembles of trees

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_gradient_boosting_oob_thumb.png
    :alt: Gradient Boosting Out-of-Bag estimates

  :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_oob.py`

Gradient Boosting Out-of-Bag estimates

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_gradient_boosting_regression_thumb.png
    :alt: Gradient Boosting regression

  :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_regression.py`

Gradient Boosting regression

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_gradient_boosting_regularization_thumb.png
    :alt: Gradient Boosting regularization

  :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_regularization.py`

Gradient Boosting regularization

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_random_forest_embedding_thumb.png
    :alt: Hashing feature transformation using Totally Random Trees

  :ref:`sphx_glr_auto_examples_ensemble_plot_random_forest_embedding.py`

Hashing feature transformation using Totally Random Trees

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_isolation_forest_thumb.png
    :alt: IsolationForest example

  :ref:`sphx_glr_auto_examples_ensemble_plot_isolation_forest.py`

IsolationForest example

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_monotonic_constraints_thumb.png
    :alt: Monotonic Constraints

  :ref:`sphx_glr_auto_examples_ensemble_plot_monotonic_constraints.py`

Monotonic Constraints

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_adaboost_multiclass_thumb.png
    :alt: Multi-class AdaBoosted Decision Trees

  :ref:`sphx_glr_auto_examples_ensemble_plot_adaboost_multiclass.py`

Multi-class AdaBoosted Decision Trees

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_ensemble_oob_thumb.png
    :alt: OOB Errors for Random Forests

  :ref:`sphx_glr_auto_examples_ensemble_plot_ensemble_oob.py`

OOB Errors for Random Forests

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_forest_importances_faces_thumb.png
    :alt: Pixel importances with a parallel forest of trees

  :ref:`sphx_glr_auto_examples_ensemble_plot_forest_importances_faces.py`

Pixel importances with a parallel forest of trees

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_voting_probas_thumb.png
    :alt: Plot class probabilities calculated by the VotingClassifier

  :ref:`sphx_glr_auto_examples_ensemble_plot_voting_probas.py`

Plot class probabilities calculated by the VotingClassifier

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_voting_regressor_thumb.png
    :alt: Plot individual and voting regression predictions

  :ref:`sphx_glr_auto_examples_ensemble_plot_voting_regressor.py`

Plot individual and voting regression predictions

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_voting_decision_regions_thumb.png
    :alt: Plot the decision boundaries of a VotingClassifier

  :ref:`sphx_glr_auto_examples_ensemble_plot_voting_decision_regions.py`

Plot the decision boundaries of a VotingClassifier

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_forest_iris_thumb.png
    :alt: Plot the decision surfaces of ensembles of trees on the iris dataset

  :ref:`sphx_glr_auto_examples_ensemble_plot_forest_iris.py`

Plot the decision surfaces of ensembles of trees on the iris dataset

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_gradient_boosting_quantile_thumb.png
    :alt: Prediction Intervals for Gradient Boosting Regression

  :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_quantile.py`

Prediction Intervals for Gradient Boosting Regression

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_bias_variance_thumb.png
    :alt: Single estimator versus bagging: bias-variance decomposition

  :ref:`sphx_glr_auto_examples_ensemble_plot_bias_variance.py`

Single estimator versus bagging: bias-variance decomposition

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  .. image:: /auto_examples/ensemble/images/thumb/sphx_glr_plot_adaboost_twoclass_thumb.png
    :alt: Two-class AdaBoost

  :ref:`sphx_glr_auto_examples_ensemble_plot_adaboost_twoclass.py`

Two-class AdaBoost

Examples based on real world datasets

Applications to real world problems with some medium sized datasets or interactive user interface.

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_tomography_l1_reconstruction_thumb.png
    :alt: Compressive sensing: tomography reconstruction with L1 prior (Lasso)

  :ref:`sphx_glr_auto_examples_applications_plot_tomography_l1_reconstruction.py`

Compressive sensing: tomography reconstruction with L1 prior (Lasso)

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_face_recognition_thumb.png
    :alt: Faces recognition example using eigenfaces and SVMs

  :ref:`sphx_glr_auto_examples_applications_plot_face_recognition.py`

Faces recognition example using eigenfaces and SVMs

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_digits_denoising_thumb.png
    :alt: Image denoising using kernel PCA

  :ref:`sphx_glr_auto_examples_applications_plot_digits_denoising.py`

Image denoising using kernel PCA

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_svm_gui_thumb.png
    :alt: Libsvm GUI

  :ref:`sphx_glr_auto_examples_applications_svm_gui.py`

Libsvm GUI

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_model_complexity_influence_thumb.png
    :alt: Model Complexity Influence

  :ref:`sphx_glr_auto_examples_applications_plot_model_complexity_influence.py`

Model Complexity Influence

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_out_of_core_classification_thumb.png
    :alt: Out-of-core classification of text documents

  :ref:`sphx_glr_auto_examples_applications_plot_out_of_core_classification.py`

Out-of-core classification of text documents

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_outlier_detection_wine_thumb.png
    :alt: Outlier detection on a real data set

  :ref:`sphx_glr_auto_examples_applications_plot_outlier_detection_wine.py`

Outlier detection on a real data set

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_prediction_latency_thumb.png
    :alt: Prediction Latency

  :ref:`sphx_glr_auto_examples_applications_plot_prediction_latency.py`

Prediction Latency

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_species_distribution_modeling_thumb.png
    :alt: Species distribution modeling

  :ref:`sphx_glr_auto_examples_applications_plot_species_distribution_modeling.py`

Species distribution modeling

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_cyclical_feature_engineering_thumb.png
    :alt: Time-related feature engineering

  :ref:`sphx_glr_auto_examples_applications_plot_cyclical_feature_engineering.py`

Time-related feature engineering

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_topics_extraction_with_nmf_lda_thumb.png
    :alt: Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation

  :ref:`sphx_glr_auto_examples_applications_plot_topics_extraction_with_nmf_lda.py`

Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_stock_market_thumb.png
    :alt: Visualizing the stock market structure

  :ref:`sphx_glr_auto_examples_applications_plot_stock_market.py`

Visualizing the stock market structure

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  .. image:: /auto_examples/applications/images/thumb/sphx_glr_wikipedia_principal_eigenvector_thumb.png
    :alt: Wikipedia principal eigenvector

  :ref:`sphx_glr_auto_examples_applications_wikipedia_principal_eigenvector.py`

Wikipedia principal eigenvector

Feature Selection

Examples concerning the :mod:`sklearn.feature_selection` module.

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  .. image:: /auto_examples/feature_selection/images/thumb/sphx_glr_plot_f_test_vs_mi_thumb.png
    :alt: Comparison of F-test and mutual information

  :ref:`sphx_glr_auto_examples_feature_selection_plot_f_test_vs_mi.py`

Comparison of F-test and mutual information

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  .. image:: /auto_examples/feature_selection/images/thumb/sphx_glr_plot_select_from_model_diabetes_thumb.png
    :alt: Model-based and sequential feature selection

  :ref:`sphx_glr_auto_examples_feature_selection_plot_select_from_model_diabetes.py`

Model-based and sequential feature selection

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  .. image:: /auto_examples/feature_selection/images/thumb/sphx_glr_plot_feature_selection_pipeline_thumb.png
    :alt: Pipeline ANOVA SVM

  :ref:`sphx_glr_auto_examples_feature_selection_plot_feature_selection_pipeline.py`

Pipeline ANOVA SVM

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  .. image:: /auto_examples/feature_selection/images/thumb/sphx_glr_plot_rfe_digits_thumb.png
    :alt: Recursive feature elimination

  :ref:`sphx_glr_auto_examples_feature_selection_plot_rfe_digits.py`

Recursive feature elimination

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  .. image:: /auto_examples/feature_selection/images/thumb/sphx_glr_plot_rfe_with_cross_validation_thumb.png
    :alt: Recursive feature elimination with cross-validation

  :ref:`sphx_glr_auto_examples_feature_selection_plot_rfe_with_cross_validation.py`

Recursive feature elimination with cross-validation

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  .. image:: /auto_examples/feature_selection/images/thumb/sphx_glr_plot_feature_selection_thumb.png
    :alt: Univariate Feature Selection

  :ref:`sphx_glr_auto_examples_feature_selection_plot_feature_selection.py`

Univariate Feature Selection

Gaussian Mixture Models

Examples concerning the :mod:`sklearn.mixture` module.

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_concentration_prior_thumb.png
    :alt: Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture

  :ref:`sphx_glr_auto_examples_mixture_plot_concentration_prior.py`

Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_gmm_pdf_thumb.png
    :alt: Density Estimation for a Gaussian mixture

  :ref:`sphx_glr_auto_examples_mixture_plot_gmm_pdf.py`

Density Estimation for a Gaussian mixture

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_gmm_init_thumb.png
    :alt: GMM Initialization Methods

  :ref:`sphx_glr_auto_examples_mixture_plot_gmm_init.py`

GMM Initialization Methods

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_gmm_covariances_thumb.png
    :alt: GMM covariances

  :ref:`sphx_glr_auto_examples_mixture_plot_gmm_covariances.py`

GMM covariances

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_gmm_thumb.png
    :alt: Gaussian Mixture Model Ellipsoids

  :ref:`sphx_glr_auto_examples_mixture_plot_gmm.py`

Gaussian Mixture Model Ellipsoids

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_gmm_selection_thumb.png
    :alt: Gaussian Mixture Model Selection

  :ref:`sphx_glr_auto_examples_mixture_plot_gmm_selection.py`

Gaussian Mixture Model Selection

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  .. image:: /auto_examples/mixture/images/thumb/sphx_glr_plot_gmm_sin_thumb.png
    :alt: Gaussian Mixture Model Sine Curve

  :ref:`sphx_glr_auto_examples_mixture_plot_gmm_sin.py`

Gaussian Mixture Model Sine Curve

Gaussian Process for Machine Learning

Examples concerning the :mod:`sklearn.gaussian_process` module.

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_compare_gpr_krr_thumb.png
    :alt: Comparison of kernel ridge and Gaussian process regression

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_compare_gpr_krr.py`

Comparison of kernel ridge and Gaussian process regression

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpr_noisy_targets_thumb.png
    :alt: Gaussian Processes regression: basic introductory example

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_noisy_targets.py`

Gaussian Processes regression: basic introductory example

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpc_iris_thumb.png
    :alt: Gaussian process classification (GPC) on iris dataset

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc_iris.py`

Gaussian process classification (GPC) on iris dataset

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpr_co2_thumb.png
    :alt: Gaussian process regression (GPR) on Mauna Loa CO2 data

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_co2.py`

Gaussian process regression (GPR) on Mauna Loa CO2 data

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpr_noisy_thumb.png
    :alt: Gaussian process regression (GPR) with noise-level estimation

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_noisy.py`

Gaussian process regression (GPR) with noise-level estimation

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpr_on_structured_data_thumb.png
    :alt: Gaussian processes on discrete data structures

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_on_structured_data.py`

Gaussian processes on discrete data structures

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpc_xor_thumb.png
    :alt: Illustration of Gaussian process classification (GPC) on the XOR dataset

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc_xor.py`

Illustration of Gaussian process classification (GPC) on the XOR dataset

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpr_prior_posterior_thumb.png
    :alt: Illustration of prior and posterior Gaussian process for different kernels

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_prior_posterior.py`

Illustration of prior and posterior Gaussian process for different kernels

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpc_isoprobability_thumb.png
    :alt: Iso-probability lines for Gaussian Processes classification (GPC)

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc_isoprobability.py`

Iso-probability lines for Gaussian Processes classification (GPC)

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  .. image:: /auto_examples/gaussian_process/images/thumb/sphx_glr_plot_gpc_thumb.png
    :alt: Probabilistic predictions with Gaussian process classification (GPC)

  :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc.py`

Probabilistic predictions with Gaussian process classification (GPC)

Generalized Linear Models

Examples concerning the :mod:`sklearn.linear_model` module.

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ard_thumb.png
    :alt: Comparing Linear Bayesian Regressors

  :ref:`sphx_glr_auto_examples_linear_model_plot_ard.py`

Comparing Linear Bayesian Regressors

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_comparison_thumb.png
    :alt: Comparing various online solvers

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_comparison.py`

Comparing various online solvers

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_bayesian_ridge_curvefit_thumb.png
    :alt: Curve Fitting with Bayesian Ridge Regression

  :ref:`sphx_glr_auto_examples_linear_model_plot_bayesian_ridge_curvefit.py`

Curve Fitting with Bayesian Ridge Regression

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_early_stopping_thumb.png
    :alt: Early stopping of Stochastic Gradient Descent

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_early_stopping.py`

Early stopping of Stochastic Gradient Descent

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_elastic_net_precomputed_gram_matrix_with_weighted_samples_thumb.png
    :alt: Fitting an Elastic Net with a precomputed Gram Matrix and Weighted Samples

  :ref:`sphx_glr_auto_examples_linear_model_plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py`

Fitting an Elastic Net with a precomputed Gram Matrix and Weighted Samples

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_huber_vs_ridge_thumb.png
    :alt: HuberRegressor vs Ridge on dataset with strong outliers

  :ref:`sphx_glr_auto_examples_linear_model_plot_huber_vs_ridge.py`

HuberRegressor vs Ridge on dataset with strong outliers

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_multi_task_lasso_support_thumb.png
    :alt: Joint feature selection with multi-task Lasso

  :ref:`sphx_glr_auto_examples_linear_model_plot_multi_task_lasso_support.py`

Joint feature selection with multi-task Lasso

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_logistic_l1_l2_sparsity_thumb.png
    :alt: L1 Penalty and Sparsity in Logistic Regression

  :ref:`sphx_glr_auto_examples_linear_model_plot_logistic_l1_l2_sparsity.py`

L1 Penalty and Sparsity in Logistic Regression

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_lasso_coordinate_descent_path_thumb.png
    :alt: Lasso and Elastic Net

  :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_coordinate_descent_path.py`

Lasso and Elastic Net

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_lasso_and_elasticnet_thumb.png
    :alt: Lasso and Elastic Net for Sparse Signals

  :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_and_elasticnet.py`

Lasso and Elastic Net for Sparse Signals

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_lasso_lars_ic_thumb.png
    :alt: Lasso model selection via information criteria

  :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_lars_ic.py`

Lasso model selection via information criteria

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_lasso_model_selection_thumb.png
    :alt: Lasso model selection: AIC-BIC / cross-validation

  :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_model_selection.py`

Lasso model selection: AIC-BIC / cross-validation

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_lasso_dense_vs_sparse_data_thumb.png
    :alt: Lasso on dense and sparse data

  :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_dense_vs_sparse_data.py`

Lasso on dense and sparse data

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_lasso_lars_thumb.png
    :alt: Lasso path using LARS

  :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_lars.py`

Lasso path using LARS

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ols_thumb.png
    :alt: Linear Regression Example

  :ref:`sphx_glr_auto_examples_linear_model_plot_ols.py`

Linear Regression Example

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_iris_logistic_thumb.png
    :alt: Logistic Regression 3-class Classifier

  :ref:`sphx_glr_auto_examples_linear_model_plot_iris_logistic.py`

Logistic Regression 3-class Classifier

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_logistic_thumb.png
    :alt: Logistic function

  :ref:`sphx_glr_auto_examples_linear_model_plot_logistic.py`

Logistic function

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sparse_logistic_regression_mnist_thumb.png
    :alt: MNIST classification using multinomial logistic + L1

  :ref:`sphx_glr_auto_examples_linear_model_plot_sparse_logistic_regression_mnist.py`

MNIST classification using multinomial logistic + L1

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sparse_logistic_regression_20newsgroups_thumb.png
    :alt: Multiclass sparse logistic regression on 20newgroups

  :ref:`sphx_glr_auto_examples_linear_model_plot_sparse_logistic_regression_20newsgroups.py`

Multiclass sparse logistic regression on 20newgroups

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_nnls_thumb.png
    :alt: Non-negative least squares

  :ref:`sphx_glr_auto_examples_linear_model_plot_nnls.py`

Non-negative least squares

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgdocsvm_vs_ocsvm_thumb.png
    :alt: One-Class SVM versus One-Class SVM using Stochastic Gradient Descent

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgdocsvm_vs_ocsvm.py`

One-Class SVM versus One-Class SVM using Stochastic Gradient Descent

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ols_ridge_variance_thumb.png
    :alt: Ordinary Least Squares and Ridge Regression Variance

  :ref:`sphx_glr_auto_examples_linear_model_plot_ols_ridge_variance.py`

Ordinary Least Squares and Ridge Regression Variance

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_omp_thumb.png
    :alt: Orthogonal Matching Pursuit

  :ref:`sphx_glr_auto_examples_linear_model_plot_omp.py`

Orthogonal Matching Pursuit

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  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ridge_coeffs_thumb.png
    :alt: Plot Ridge coefficients as a function of the L2 regularization

  :ref:`sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py`

Plot Ridge coefficients as a function of the L2 regularization

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ridge_path_thumb.png
    :alt: Plot Ridge coefficients as a function of the regularization

  :ref:`sphx_glr_auto_examples_linear_model_plot_ridge_path.py`

Plot Ridge coefficients as a function of the regularization

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_iris_thumb.png
    :alt: Plot multi-class SGD on the iris dataset

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_iris.py`

Plot multi-class SGD on the iris dataset

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_logistic_multinomial_thumb.png
    :alt: Plot multinomial and One-vs-Rest Logistic Regression

  :ref:`sphx_glr_auto_examples_linear_model_plot_logistic_multinomial.py`

Plot multinomial and One-vs-Rest Logistic Regression

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_poisson_regression_non_normal_loss_thumb.png
    :alt: Poisson regression and non-normal loss

  :ref:`sphx_glr_auto_examples_linear_model_plot_poisson_regression_non_normal_loss.py`

Poisson regression and non-normal loss

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_polynomial_interpolation_thumb.png
    :alt: Polynomial and Spline interpolation

  :ref:`sphx_glr_auto_examples_linear_model_plot_polynomial_interpolation.py`

Polynomial and Spline interpolation

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_quantile_regression_thumb.png
    :alt: Quantile regression

  :ref:`sphx_glr_auto_examples_linear_model_plot_quantile_regression.py`

Quantile regression

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_logistic_path_thumb.png
    :alt: Regularization path of L1- Logistic Regression

  :ref:`sphx_glr_auto_examples_linear_model_plot_logistic_path.py`

Regularization path of L1- Logistic Regression

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_robust_fit_thumb.png
    :alt: Robust linear estimator fitting

  :ref:`sphx_glr_auto_examples_linear_model_plot_robust_fit.py`

Robust linear estimator fitting

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ransac_thumb.png
    :alt: Robust linear model estimation using RANSAC

  :ref:`sphx_glr_auto_examples_linear_model_plot_ransac.py`

Robust linear model estimation using RANSAC

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_separating_hyperplane_thumb.png
    :alt: SGD: Maximum margin separating hyperplane

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_separating_hyperplane.py`

SGD: Maximum margin separating hyperplane

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_penalties_thumb.png
    :alt: SGD: Penalties

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_penalties.py`

SGD: Penalties

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_weighted_samples_thumb.png
    :alt: SGD: Weighted samples

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_weighted_samples.py`

SGD: Weighted samples

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_sgd_loss_functions_thumb.png
    :alt: SGD: convex loss functions

  :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_loss_functions.py`

SGD: convex loss functions

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_ols_3d_thumb.png
    :alt: Sparsity Example: Fitting only features 1  and 2

  :ref:`sphx_glr_auto_examples_linear_model_plot_ols_3d.py`

Sparsity Example: Fitting only features 1 and 2

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_theilsen_thumb.png
    :alt: Theil-Sen Regression

  :ref:`sphx_glr_auto_examples_linear_model_plot_theilsen.py`

Theil-Sen Regression

.. only:: html

  .. image:: /auto_examples/linear_model/images/thumb/sphx_glr_plot_tweedie_regression_insurance_claims_thumb.png
    :alt: Tweedie regression on insurance claims

  :ref:`sphx_glr_auto_examples_linear_model_plot_tweedie_regression_insurance_claims.py`

Tweedie regression on insurance claims

Inspection

Examples related to the :mod:`sklearn.inspection` module.

.. only:: html

  .. image:: /auto_examples/inspection/images/thumb/sphx_glr_plot_linear_model_coefficient_interpretation_thumb.png
    :alt: Common pitfalls in the interpretation of coefficients of linear models

  :ref:`sphx_glr_auto_examples_inspection_plot_linear_model_coefficient_interpretation.py`

Common pitfalls in the interpretation of coefficients of linear models

.. only:: html

  .. image:: /auto_examples/inspection/images/thumb/sphx_glr_plot_partial_dependence_thumb.png
    :alt: Partial Dependence and Individual Conditional Expectation Plots

  :ref:`sphx_glr_auto_examples_inspection_plot_partial_dependence.py`

Partial Dependence and Individual Conditional Expectation Plots

.. only:: html

  .. image:: /auto_examples/inspection/images/thumb/sphx_glr_plot_permutation_importance_thumb.png
    :alt: Permutation Importance vs Random Forest Feature Importance (MDI)

  :ref:`sphx_glr_auto_examples_inspection_plot_permutation_importance.py`

Permutation Importance vs Random Forest Feature Importance (MDI)

.. only:: html

  .. image:: /auto_examples/inspection/images/thumb/sphx_glr_plot_permutation_importance_multicollinear_thumb.png
    :alt: Permutation Importance with Multicollinear or Correlated Features

  :ref:`sphx_glr_auto_examples_inspection_plot_permutation_importance_multicollinear.py`

Permutation Importance with Multicollinear or Correlated Features

Kernel Approximation

Examples concerning the :mod:`sklearn.kernel_approximation` module.

.. only:: html

  .. image:: /auto_examples/kernel_approximation/images/thumb/sphx_glr_plot_scalable_poly_kernels_thumb.png
    :alt: Scalable learning with polynomial kernel approximation

  :ref:`sphx_glr_auto_examples_kernel_approximation_plot_scalable_poly_kernels.py`

Scalable learning with polynomial kernel approximation

Manifold learning

Examples concerning the :mod:`sklearn.manifold` module.

.. only:: html

  .. image:: /auto_examples/manifold/images/thumb/sphx_glr_plot_compare_methods_thumb.png
    :alt: Comparison of Manifold Learning methods

  :ref:`sphx_glr_auto_examples_manifold_plot_compare_methods.py`

Comparison of Manifold Learning methods

.. only:: html

  .. image:: /auto_examples/manifold/images/thumb/sphx_glr_plot_manifold_sphere_thumb.png
    :alt: Manifold Learning methods on a severed sphere

  :ref:`sphx_glr_auto_examples_manifold_plot_manifold_sphere.py`

Manifold Learning methods on a severed sphere

.. only:: html

  .. image:: /auto_examples/manifold/images/thumb/sphx_glr_plot_lle_digits_thumb.png
    :alt: Manifold learning on handwritten digits: Locally Linear Embedding, Isomap...

  :ref:`sphx_glr_auto_examples_manifold_plot_lle_digits.py`

Manifold learning on handwritten digits: Locally Linear Embedding, Isomap...

.. only:: html

  .. image:: /auto_examples/manifold/images/thumb/sphx_glr_plot_mds_thumb.png
    :alt: Multi-dimensional scaling

  :ref:`sphx_glr_auto_examples_manifold_plot_mds.py`

Multi-dimensional scaling

.. only:: html

  .. image:: /auto_examples/manifold/images/thumb/sphx_glr_plot_swissroll_thumb.png
    :alt: Swiss Roll And Swiss-Hole Reduction

  :ref:`sphx_glr_auto_examples_manifold_plot_swissroll.py`

Swiss Roll And Swiss-Hole Reduction

.. only:: html

  .. image:: /auto_examples/manifold/images/thumb/sphx_glr_plot_t_sne_perplexity_thumb.png
    :alt: t-SNE: The effect of various perplexity values on the shape

  :ref:`sphx_glr_auto_examples_manifold_plot_t_sne_perplexity.py`

t-SNE: The effect of various perplexity values on the shape

Miscellaneous

Miscellaneous and introductory examples for scikit-learn.

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_partial_dependence_visualization_api_thumb.png
    :alt: Advanced Plotting With Partial Dependence

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_partial_dependence_visualization_api.py`

Advanced Plotting With Partial Dependence

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_changed_only_pprint_parameter_thumb.png
    :alt: Compact estimator representations

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_changed_only_pprint_parameter.py`

Compact estimator representations

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_anomaly_comparison_thumb.png
    :alt: Comparing anomaly detection algorithms for outlier detection on toy datasets

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_anomaly_comparison.py`

Comparing anomaly detection algorithms for outlier detection on toy datasets

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_kernel_ridge_regression_thumb.png
    :alt: Comparison of kernel ridge regression and SVR

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_kernel_ridge_regression.py`

Comparison of kernel ridge regression and SVR

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_pipeline_display_thumb.png
    :alt: Displaying Pipelines

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_pipeline_display.py`

Displaying Pipelines

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_outlier_detection_bench_thumb.png
    :alt: Evaluation of outlier detection estimators

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_outlier_detection_bench.py`

Evaluation of outlier detection estimators

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_kernel_approximation_thumb.png
    :alt: Explicit feature map approximation for RBF kernels

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_kernel_approximation.py`

Explicit feature map approximation for RBF kernels

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_multioutput_face_completion_thumb.png
    :alt: Face completion with a multi-output estimators

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_multioutput_face_completion.py`

Face completion with a multi-output estimators

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_isotonic_regression_thumb.png
    :alt: Isotonic Regression

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_isotonic_regression.py`

Isotonic Regression

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_multilabel_thumb.png
    :alt: Multilabel classification

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_multilabel.py`

Multilabel classification

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_roc_curve_visualization_api_thumb.png
    :alt: ROC Curve with Visualization API

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_roc_curve_visualization_api.py`

ROC Curve with Visualization API

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_johnson_lindenstrauss_bound_thumb.png
    :alt: The Johnson-Lindenstrauss bound for embedding with random projections

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_johnson_lindenstrauss_bound.py`

The Johnson-Lindenstrauss bound for embedding with random projections

.. only:: html

  .. image:: /auto_examples/miscellaneous/images/thumb/sphx_glr_plot_display_object_visualization_thumb.png
    :alt: Visualizations with Display Objects

  :ref:`sphx_glr_auto_examples_miscellaneous_plot_display_object_visualization.py`

Visualizations with Display Objects

Missing Value Imputation

Examples concerning the :mod:`sklearn.impute` module.

.. only:: html

  .. image:: /auto_examples/impute/images/thumb/sphx_glr_plot_missing_values_thumb.png
    :alt: Imputing missing values before building an estimator

  :ref:`sphx_glr_auto_examples_impute_plot_missing_values.py`

Imputing missing values before building an estimator

.. only:: html

  .. image:: /auto_examples/impute/images/thumb/sphx_glr_plot_iterative_imputer_variants_comparison_thumb.png
    :alt: Imputing missing values with variants of IterativeImputer

  :ref:`sphx_glr_auto_examples_impute_plot_iterative_imputer_variants_comparison.py`

Imputing missing values with variants of IterativeImputer

Model Selection

Examples related to the :mod:`sklearn.model_selection` module.

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_grid_search_refit_callable_thumb.png
    :alt: Balance model complexity and cross-validated score

  :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_refit_callable.py`

Balance model complexity and cross-validated score

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_randomized_search_thumb.png
    :alt: Comparing randomized search and grid search for hyperparameter estimation

  :ref:`sphx_glr_auto_examples_model_selection_plot_randomized_search.py`

Comparing randomized search and grid search for hyperparameter estimation

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_successive_halving_heatmap_thumb.png
    :alt: Comparison between grid search and successive halving

  :ref:`sphx_glr_auto_examples_model_selection_plot_successive_halving_heatmap.py`

Comparison between grid search and successive halving

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_confusion_matrix_thumb.png
    :alt: Confusion matrix

  :ref:`sphx_glr_auto_examples_model_selection_plot_confusion_matrix.py`

Confusion matrix

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_grid_search_digits_thumb.png
    :alt: Custom refit strategy of a grid search with cross-validation

  :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_digits.py`

Custom refit strategy of a grid search with cross-validation

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_multi_metric_evaluation_thumb.png
    :alt: Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV

  :ref:`sphx_glr_auto_examples_model_selection_plot_multi_metric_evaluation.py`

Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_det_thumb.png
    :alt: Detection error tradeoff (DET) curve

  :ref:`sphx_glr_auto_examples_model_selection_plot_det.py`

Detection error tradeoff (DET) curve

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_nested_cross_validation_iris_thumb.png
    :alt: Nested versus non-nested cross-validation

  :ref:`sphx_glr_auto_examples_model_selection_plot_nested_cross_validation_iris.py`

Nested versus non-nested cross-validation

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_cv_predict_thumb.png
    :alt: Plotting Cross-Validated Predictions

  :ref:`sphx_glr_auto_examples_model_selection_plot_cv_predict.py`

Plotting Cross-Validated Predictions

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_learning_curve_thumb.png
    :alt: Plotting Learning Curves

  :ref:`sphx_glr_auto_examples_model_selection_plot_learning_curve.py`

Plotting Learning Curves

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_validation_curve_thumb.png
    :alt: Plotting Validation Curves

  :ref:`sphx_glr_auto_examples_model_selection_plot_validation_curve.py`

Plotting Validation Curves

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_precision_recall_thumb.png
    :alt: Precision-Recall

  :ref:`sphx_glr_auto_examples_model_selection_plot_precision_recall.py`

Precision-Recall

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_roc_thumb.png
    :alt: Receiver Operating Characteristic (ROC)

  :ref:`sphx_glr_auto_examples_model_selection_plot_roc.py`

Receiver Operating Characteristic (ROC)

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_roc_crossval_thumb.png
    :alt: Receiver Operating Characteristic (ROC) with cross validation

  :ref:`sphx_glr_auto_examples_model_selection_plot_roc_crossval.py`

Receiver Operating Characteristic (ROC) with cross validation

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_grid_search_text_feature_extraction_thumb.png
    :alt: Sample pipeline for text feature extraction and evaluation

  :ref:`sphx_glr_auto_examples_model_selection_grid_search_text_feature_extraction.py`

Sample pipeline for text feature extraction and evaluation

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_grid_search_stats_thumb.png
    :alt: Statistical comparison of models using grid search

  :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_stats.py`

Statistical comparison of models using grid search

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_successive_halving_iterations_thumb.png
    :alt: Successive Halving Iterations

  :ref:`sphx_glr_auto_examples_model_selection_plot_successive_halving_iterations.py`

Successive Halving Iterations

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_permutation_tests_for_classification_thumb.png
    :alt: Test with permutations the significance of a classification score

  :ref:`sphx_glr_auto_examples_model_selection_plot_permutation_tests_for_classification.py`

Test with permutations the significance of a classification score

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_train_error_vs_test_error_thumb.png
    :alt: Train error vs Test error

  :ref:`sphx_glr_auto_examples_model_selection_plot_train_error_vs_test_error.py`

Train error vs Test error

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_underfitting_overfitting_thumb.png
    :alt: Underfitting vs. Overfitting

  :ref:`sphx_glr_auto_examples_model_selection_plot_underfitting_overfitting.py`

Underfitting vs. Overfitting

.. only:: html

  .. image:: /auto_examples/model_selection/images/thumb/sphx_glr_plot_cv_indices_thumb.png
    :alt: Visualizing cross-validation behavior in scikit-learn

  :ref:`sphx_glr_auto_examples_model_selection_plot_cv_indices.py`

Visualizing cross-validation behavior in scikit-learn

Multioutput methods

Examples concerning the :mod:`sklearn.multioutput` module.

.. only:: html

  .. image:: /auto_examples/multioutput/images/thumb/sphx_glr_plot_classifier_chain_yeast_thumb.png
    :alt: Classifier Chain

  :ref:`sphx_glr_auto_examples_multioutput_plot_classifier_chain_yeast.py`

Classifier Chain

Nearest Neighbors

Examples concerning the :mod:`sklearn.neighbors` module.

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_approximate_nearest_neighbors_thumb.png
    :alt: Approximate nearest neighbors in TSNE

  :ref:`sphx_glr_auto_examples_neighbors_approximate_nearest_neighbors.py`

Approximate nearest neighbors in TSNE

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_caching_nearest_neighbors_thumb.png
    :alt: Caching nearest neighbors

  :ref:`sphx_glr_auto_examples_neighbors_plot_caching_nearest_neighbors.py`

Caching nearest neighbors

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_nca_classification_thumb.png
    :alt: Comparing Nearest Neighbors with and without Neighborhood Components Analysis

  :ref:`sphx_glr_auto_examples_neighbors_plot_nca_classification.py`

Comparing Nearest Neighbors with and without Neighborhood Components Analysis

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_nca_dim_reduction_thumb.png
    :alt: Dimensionality Reduction with Neighborhood Components Analysis

  :ref:`sphx_glr_auto_examples_neighbors_plot_nca_dim_reduction.py`

Dimensionality Reduction with Neighborhood Components Analysis

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_species_kde_thumb.png
    :alt: Kernel Density Estimate of Species Distributions

  :ref:`sphx_glr_auto_examples_neighbors_plot_species_kde.py`

Kernel Density Estimate of Species Distributions

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_digits_kde_sampling_thumb.png
    :alt: Kernel Density Estimation

  :ref:`sphx_glr_auto_examples_neighbors_plot_digits_kde_sampling.py`

Kernel Density Estimation

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_nearest_centroid_thumb.png
    :alt: Nearest Centroid Classification

  :ref:`sphx_glr_auto_examples_neighbors_plot_nearest_centroid.py`

Nearest Centroid Classification

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_classification_thumb.png
    :alt: Nearest Neighbors Classification

  :ref:`sphx_glr_auto_examples_neighbors_plot_classification.py`

Nearest Neighbors Classification

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_regression_thumb.png
    :alt: Nearest Neighbors regression

  :ref:`sphx_glr_auto_examples_neighbors_plot_regression.py`

Nearest Neighbors regression

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_nca_illustration_thumb.png
    :alt: Neighborhood Components Analysis Illustration

  :ref:`sphx_glr_auto_examples_neighbors_plot_nca_illustration.py`

Neighborhood Components Analysis Illustration

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_lof_novelty_detection_thumb.png
    :alt: Novelty detection with Local Outlier Factor (LOF)

  :ref:`sphx_glr_auto_examples_neighbors_plot_lof_novelty_detection.py`

Novelty detection with Local Outlier Factor (LOF)

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_lof_outlier_detection_thumb.png
    :alt: Outlier detection with Local Outlier Factor (LOF)

  :ref:`sphx_glr_auto_examples_neighbors_plot_lof_outlier_detection.py`

Outlier detection with Local Outlier Factor (LOF)

.. only:: html

  .. image:: /auto_examples/neighbors/images/thumb/sphx_glr_plot_kde_1d_thumb.png
    :alt: Simple 1D Kernel Density Estimation

  :ref:`sphx_glr_auto_examples_neighbors_plot_kde_1d.py`

Simple 1D Kernel Density Estimation

Neural Networks

Examples concerning the :mod:`sklearn.neural_network` module.

.. only:: html

  .. image:: /auto_examples/neural_networks/images/thumb/sphx_glr_plot_mlp_training_curves_thumb.png
    :alt: Compare Stochastic learning strategies for MLPClassifier

  :ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_training_curves.py`

Compare Stochastic learning strategies for MLPClassifier

.. only:: html

  .. image:: /auto_examples/neural_networks/images/thumb/sphx_glr_plot_rbm_logistic_classification_thumb.png
    :alt: Restricted Boltzmann Machine features for digit classification

  :ref:`sphx_glr_auto_examples_neural_networks_plot_rbm_logistic_classification.py`

Restricted Boltzmann Machine features for digit classification

.. only:: html

  .. image:: /auto_examples/neural_networks/images/thumb/sphx_glr_plot_mlp_alpha_thumb.png
    :alt: Varying regularization in Multi-layer Perceptron

  :ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_alpha.py`

Varying regularization in Multi-layer Perceptron

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  .. image:: /auto_examples/neural_networks/images/thumb/sphx_glr_plot_mnist_filters_thumb.png
    :alt: Visualization of MLP weights on MNIST

  :ref:`sphx_glr_auto_examples_neural_networks_plot_mnist_filters.py`

Visualization of MLP weights on MNIST

Pipelines and composite estimators

Examples of how to compose transformers and pipelines from other estimators. See the :ref:`User Guide <combining_estimators>`.

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  .. image:: /auto_examples/compose/images/thumb/sphx_glr_plot_column_transformer_thumb.png
    :alt: Column Transformer with Heterogeneous Data Sources

  :ref:`sphx_glr_auto_examples_compose_plot_column_transformer.py`

Column Transformer with Heterogeneous Data Sources

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  .. image:: /auto_examples/compose/images/thumb/sphx_glr_plot_column_transformer_mixed_types_thumb.png
    :alt: Column Transformer with Mixed Types

  :ref:`sphx_glr_auto_examples_compose_plot_column_transformer_mixed_types.py`

Column Transformer with Mixed Types

.. only:: html

  .. image:: /auto_examples/compose/images/thumb/sphx_glr_plot_feature_union_thumb.png
    :alt: Concatenating multiple feature extraction methods

  :ref:`sphx_glr_auto_examples_compose_plot_feature_union.py`

Concatenating multiple feature extraction methods

.. only:: html

  .. image:: /auto_examples/compose/images/thumb/sphx_glr_plot_transformed_target_thumb.png
    :alt: Effect of transforming the targets in regression model

  :ref:`sphx_glr_auto_examples_compose_plot_transformed_target.py`

Effect of transforming the targets in regression model

.. only:: html

  .. image:: /auto_examples/compose/images/thumb/sphx_glr_plot_digits_pipe_thumb.png
    :alt: Pipelining: chaining a PCA and a logistic regression

  :ref:`sphx_glr_auto_examples_compose_plot_digits_pipe.py`

Pipelining: chaining a PCA and a logistic regression

.. only:: html

  .. image:: /auto_examples/compose/images/thumb/sphx_glr_plot_compare_reduction_thumb.png
    :alt: Selecting dimensionality reduction with Pipeline and GridSearchCV

  :ref:`sphx_glr_auto_examples_compose_plot_compare_reduction.py`

Selecting dimensionality reduction with Pipeline and GridSearchCV

Preprocessing

Examples concerning the :mod:`sklearn.preprocessing` module.

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  .. image:: /auto_examples/preprocessing/images/thumb/sphx_glr_plot_all_scaling_thumb.png
    :alt: Compare the effect of different scalers on data with outliers

  :ref:`sphx_glr_auto_examples_preprocessing_plot_all_scaling.py`

Compare the effect of different scalers on data with outliers

.. only:: html

  .. image:: /auto_examples/preprocessing/images/thumb/sphx_glr_plot_discretization_strategies_thumb.png
    :alt: Demonstrating the different strategies of KBinsDiscretizer

  :ref:`sphx_glr_auto_examples_preprocessing_plot_discretization_strategies.py`

Demonstrating the different strategies of KBinsDiscretizer

.. only:: html

  .. image:: /auto_examples/preprocessing/images/thumb/sphx_glr_plot_discretization_classification_thumb.png
    :alt: Feature discretization

  :ref:`sphx_glr_auto_examples_preprocessing_plot_discretization_classification.py`

Feature discretization

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  .. image:: /auto_examples/preprocessing/images/thumb/sphx_glr_plot_scaling_importance_thumb.png
    :alt: Importance of Feature Scaling

  :ref:`sphx_glr_auto_examples_preprocessing_plot_scaling_importance.py`

Importance of Feature Scaling

.. only:: html

  .. image:: /auto_examples/preprocessing/images/thumb/sphx_glr_plot_map_data_to_normal_thumb.png
    :alt: Map data to a normal distribution

  :ref:`sphx_glr_auto_examples_preprocessing_plot_map_data_to_normal.py`

Map data to a normal distribution

.. only:: html

  .. image:: /auto_examples/preprocessing/images/thumb/sphx_glr_plot_discretization_thumb.png
    :alt: Using KBinsDiscretizer to discretize continuous features

  :ref:`sphx_glr_auto_examples_preprocessing_plot_discretization.py`

Using KBinsDiscretizer to discretize continuous features

Semi Supervised Classification

Examples concerning the :mod:`sklearn.semi_supervised` module.

.. only:: html

  .. image:: /auto_examples/semi_supervised/images/thumb/sphx_glr_plot_semi_supervised_versus_svm_iris_thumb.png
    :alt: Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset

  :ref:`sphx_glr_auto_examples_semi_supervised_plot_semi_supervised_versus_svm_iris.py`

Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset

.. only:: html

  .. image:: /auto_examples/semi_supervised/images/thumb/sphx_glr_plot_self_training_varying_threshold_thumb.png
    :alt: Effect of varying threshold for self-training

  :ref:`sphx_glr_auto_examples_semi_supervised_plot_self_training_varying_threshold.py`

Effect of varying threshold for self-training

.. only:: html

  .. image:: /auto_examples/semi_supervised/images/thumb/sphx_glr_plot_label_propagation_digits_active_learning_thumb.png
    :alt: Label Propagation digits active learning

  :ref:`sphx_glr_auto_examples_semi_supervised_plot_label_propagation_digits_active_learning.py`

Label Propagation digits active learning

.. only:: html

  .. image:: /auto_examples/semi_supervised/images/thumb/sphx_glr_plot_label_propagation_digits_thumb.png
    :alt: Label Propagation digits: Demonstrating performance

  :ref:`sphx_glr_auto_examples_semi_supervised_plot_label_propagation_digits.py`

Label Propagation digits: Demonstrating performance

.. only:: html

  .. image:: /auto_examples/semi_supervised/images/thumb/sphx_glr_plot_label_propagation_structure_thumb.png
    :alt: Label Propagation learning a complex structure

  :ref:`sphx_glr_auto_examples_semi_supervised_plot_label_propagation_structure.py`

Label Propagation learning a complex structure

.. only:: html

  .. image:: /auto_examples/semi_supervised/images/thumb/sphx_glr_plot_semi_supervised_newsgroups_thumb.png
    :alt: Semi-supervised Classification on a Text Dataset

  :ref:`sphx_glr_auto_examples_semi_supervised_plot_semi_supervised_newsgroups.py`

Semi-supervised Classification on a Text Dataset

Support Vector Machines

Examples concerning the :mod:`sklearn.svm` module.

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_nonlinear_thumb.png
    :alt: Non-linear SVM

  :ref:`sphx_glr_auto_examples_svm_plot_svm_nonlinear.py`

Non-linear SVM

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_oneclass_thumb.png
    :alt: One-class SVM with non-linear kernel (RBF)

  :ref:`sphx_glr_auto_examples_svm_plot_oneclass.py`

One-class SVM with non-linear kernel (RBF)

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_iris_svc_thumb.png
    :alt: Plot different SVM classifiers in the iris dataset

  :ref:`sphx_glr_auto_examples_svm_plot_iris_svc.py`

Plot different SVM classifiers in the iris dataset

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_linearsvc_support_vectors_thumb.png
    :alt: Plot the support vectors in LinearSVC

  :ref:`sphx_glr_auto_examples_svm_plot_linearsvc_support_vectors.py`

Plot the support vectors in LinearSVC

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_rbf_parameters_thumb.png
    :alt: RBF SVM parameters

  :ref:`sphx_glr_auto_examples_svm_plot_rbf_parameters.py`

RBF SVM parameters

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_margin_thumb.png
    :alt: SVM Margins Example

  :ref:`sphx_glr_auto_examples_svm_plot_svm_margin.py`

SVM Margins Example

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_tie_breaking_thumb.png
    :alt: SVM Tie Breaking Example

  :ref:`sphx_glr_auto_examples_svm_plot_svm_tie_breaking.py`

SVM Tie Breaking Example

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_custom_kernel_thumb.png
    :alt: SVM with custom kernel

  :ref:`sphx_glr_auto_examples_svm_plot_custom_kernel.py`

SVM with custom kernel

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_anova_thumb.png
    :alt: SVM-Anova: SVM with univariate feature selection

  :ref:`sphx_glr_auto_examples_svm_plot_svm_anova.py`

SVM-Anova: SVM with univariate feature selection

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_kernels_thumb.png
    :alt: SVM-Kernels

  :ref:`sphx_glr_auto_examples_svm_plot_svm_kernels.py`

SVM-Kernels

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_separating_hyperplane_thumb.png
    :alt: SVM: Maximum margin separating hyperplane

  :ref:`sphx_glr_auto_examples_svm_plot_separating_hyperplane.py`

SVM: Maximum margin separating hyperplane

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_separating_hyperplane_unbalanced_thumb.png
    :alt: SVM: Separating hyperplane for unbalanced classes

  :ref:`sphx_glr_auto_examples_svm_plot_separating_hyperplane_unbalanced.py`

SVM: Separating hyperplane for unbalanced classes

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_weighted_samples_thumb.png
    :alt: SVM: Weighted samples

  :ref:`sphx_glr_auto_examples_svm_plot_weighted_samples.py`

SVM: Weighted samples

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_scale_c_thumb.png
    :alt: Scaling the regularization parameter for SVCs

  :ref:`sphx_glr_auto_examples_svm_plot_svm_scale_c.py`

Scaling the regularization parameter for SVCs

.. only:: html

  .. image:: /auto_examples/svm/images/thumb/sphx_glr_plot_svm_regression_thumb.png
    :alt: Support Vector Regression (SVR) using linear and non-linear kernels

  :ref:`sphx_glr_auto_examples_svm_plot_svm_regression.py`

Support Vector Regression (SVR) using linear and non-linear kernels

Tutorial exercises

Exercises for the tutorials

.. only:: html

  .. image:: /auto_examples/exercises/images/thumb/sphx_glr_plot_cv_digits_thumb.png
    :alt: Cross-validation on Digits Dataset Exercise

  :ref:`sphx_glr_auto_examples_exercises_plot_cv_digits.py`

Cross-validation on Digits Dataset Exercise

.. only:: html

  .. image:: /auto_examples/exercises/images/thumb/sphx_glr_plot_cv_diabetes_thumb.png
    :alt: Cross-validation on diabetes Dataset Exercise

  :ref:`sphx_glr_auto_examples_exercises_plot_cv_diabetes.py`

Cross-validation on diabetes Dataset Exercise

.. only:: html

  .. image:: /auto_examples/exercises/images/thumb/sphx_glr_plot_digits_classification_exercise_thumb.png
    :alt: Digits Classification Exercise

  :ref:`sphx_glr_auto_examples_exercises_plot_digits_classification_exercise.py`

Digits Classification Exercise

.. only:: html

  .. image:: /auto_examples/exercises/images/thumb/sphx_glr_plot_iris_exercise_thumb.png
    :alt: SVM Exercise

  :ref:`sphx_glr_auto_examples_exercises_plot_iris_exercise.py`

SVM Exercise

Working with text documents

Examples concerning the :mod:`sklearn.feature_extraction.text` module.

.. only:: html

  .. image:: /auto_examples/text/images/thumb/sphx_glr_plot_document_classification_20newsgroups_thumb.png
    :alt: Classification of text documents using sparse features

  :ref:`sphx_glr_auto_examples_text_plot_document_classification_20newsgroups.py`

Classification of text documents using sparse features

.. only:: html

  .. image:: /auto_examples/text/images/thumb/sphx_glr_plot_document_clustering_thumb.png
    :alt: Clustering text documents using k-means

  :ref:`sphx_glr_auto_examples_text_plot_document_clustering.py`

Clustering text documents using k-means

.. only:: html

  .. image:: /auto_examples/text/images/thumb/sphx_glr_plot_hashing_vs_dict_vectorizer_thumb.png
    :alt: FeatureHasher and DictVectorizer Comparison

  :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py`

FeatureHasher and DictVectorizer Comparison

.. toctree::
   :hidden:
   :includehidden:

   /auto_examples/release_highlights/index.rst
   /auto_examples/bicluster/index.rst
   /auto_examples/calibration/index.rst
   /auto_examples/classification/index.rst
   /auto_examples/cluster/index.rst
   /auto_examples/covariance/index.rst
   /auto_examples/cross_decomposition/index.rst
   /auto_examples/datasets/index.rst
   /auto_examples/tree/index.rst
   /auto_examples/decomposition/index.rst
   /auto_examples/ensemble/index.rst
   /auto_examples/applications/index.rst
   /auto_examples/feature_selection/index.rst
   /auto_examples/mixture/index.rst
   /auto_examples/gaussian_process/index.rst
   /auto_examples/linear_model/index.rst
   /auto_examples/inspection/index.rst
   /auto_examples/kernel_approximation/index.rst
   /auto_examples/manifold/index.rst
   /auto_examples/miscellaneous/index.rst
   /auto_examples/impute/index.rst
   /auto_examples/model_selection/index.rst
   /auto_examples/multioutput/index.rst
   /auto_examples/neighbors/index.rst
   /auto_examples/neural_networks/index.rst
   /auto_examples/compose/index.rst
   /auto_examples/preprocessing/index.rst
   /auto_examples/semi_supervised/index.rst
   /auto_examples/svm/index.rst
   /auto_examples/exercises/index.rst
   /auto_examples/text/index.rst

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-gallery

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download all examples in Python source code: auto_examples_python.zip </auto_examples/auto_examples_python.zip>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download all examples in Jupyter notebooks: auto_examples_jupyter.zip </auto_examples/auto_examples_jupyter.zip>`

.. only:: html

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

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_