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This documentation is for scikit-learn version 0.13 — Other versions

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Examples

Examples¶

General examples¶

General-purpose and introductory examples for the scikit.

../_images/plot_classification_probability.png

Plot classification probability

../_images/plot_classifier_comparison.png

Classifiers Comparison

../_images/plot_confusion_matrix.png

Confusion matrix

../_images/plot_digits_classification.png

Recognizing hand-written digits

../_images/plot_digits_pipe.png

Pipelining: chaining a PCA and a logistic regression

../_images/plot_feature_selection.png

Univariate Feature Selection

../_images/plot_hmm_sampling.png

Demonstration of sampling from HMM

../_images/plot_hmm_stock_analysis.png

Gaussian HMM of stock data

../_images/plot_isotonic_regression.png

Isotonic Regression

../_images/plot_johnson_lindenstrauss_bound.png

The Johnson-Lindenstrauss bound for embedding with random projections

../_images/plot_kernel_approximation.png

Explicit feature map approximation for RBF kernels

../_images/plot_lda_qda.png

Linear and Quadratic Discriminant Analysis with confidence ellipsoid

../_images/plot_multilabel.png

Multilabel classification

../_images/plot_permutation_test_for_classification.png

Test with permutations the significance of a classification score

../_images/plot_pls.png

PLS Partial Least Squares

../_images/plot_precision_recall.png

Precision-Recall

../_images/plot_rfe_digits.png

Recursive feature elimination

../_images/plot_rfe_with_cross_validation.png

Recursive feature elimination with cross-validation

../_images/plot_roc.png

Receiver operating characteristic (ROC)

../_images/plot_roc_crossval.png

Receiver operating characteristic (ROC) with cross validation

../_images/plot_train_error_vs_test_error.png

Train error vs Test error

../_images/document_classification_20newsgroups.png

Classification of text documents using sparse features

../_images/document_clustering.png

Clustering text documents using k-means

../_images/feature_selection_pipeline.png

Pipeline Anova SVM

../_images/feature_stacker.png

Concatenating multiple feature extraction methods

../_images/grid_search_digits.png

Parameter estimation using grid search with a nested cross-validation

../_images/grid_search_text_feature_extraction.png

Sample pipeline for text feature extraction and evaluation

../_images/hashing_vs_dict_vectorizer.png

Comparison of hashing-based and dictionary based text vectorization

../_images/mlcomp_sparse_document_classification.png

Classification of text documents: using a MLComp dataset

Examples based on real world datasets¶

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

../_images/plot_outlier_detection_housing.png

Outlier detection on a real data set

../_images/plot_species_distribution_modeling.png

Species distribution modeling

../_images/plot_stock_market.png

Visualizing the stock market structure

../_images/plot_tomography_l1_reconstruction.png

Compressive sensing: tomography reconstruction with L1 prior (Lasso)

../_images/face_recognition.png

Faces recognition example using eigenfaces and SVMs

../_images/svm_gui.png

../_images/topics_extraction_with_nmf.png

Topics extraction with Non-Negative Matrix Factorization

../_images/wikipedia_principal_eigenvector.png

Wikipedia principal eigenvector

Clustering¶

Examples concerning the sklearn.cluster package.

../_images/plot_adjusted_for_chance_measures.png

Adjustment for chance in clustering performance evaluation

../_images/plot_affinity_propagation.png

Demo of affinity propagation clustering algorithm

../_images/plot_cluster_comparison.png

Comparing different clustering algorithms on toy datasets

../_images/plot_cluster_iris.png

K-means Clustering

../_images/plot_color_quantization.png

Color Quantization using K-Means

../_images/plot_dbscan.png

Demo of DBSCAN clustering algorithm

../_images/plot_dict_face_patches.png

Online learning of a dictionary of parts of faces

../_images/plot_digits_agglomeration.png

Feature agglomeration

../_images/plot_feature_agglomeration_vs_univariate_selection.png

Feature agglomeration vs. univariate selection

../_images/plot_kmeans_digits.png

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

../_images/plot_kmeans_stability_low_dim_dense.png

Empirical evaluation of the impact of k-means initialization

../_images/plot_lena_compress.png

Vector Quantization Example

../_images/plot_lena_segmentation.png

Segmenting the picture of Lena in regions

../_images/plot_lena_ward_segmentation.png

A demo of structured Ward hierarchical clustering on Lena image

../_images/plot_mean_shift.png

A demo of the mean-shift clustering algorithm

../_images/plot_mini_batch_kmeans.png

A demo of the K Means clustering algorithm

../_images/plot_segmentation_toy.png

Spectral clustering for image segmentation

../_images/plot_ward_structured_vs_unstructured.png

Hierarchical clustering: structured vs unstructured ward

Covariance estimation¶

Examples concerning the sklearn.covariance package.

../_images/plot_covariance_estimation.png

Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood

../_images/plot_lw_vs_oas.png

Ledoit-Wolf vs OAS estimation

../_images/plot_mahalanobis_distances.png

Robust covariance estimation and Mahalanobis distances relevance

../_images/plot_outlier_detection.png

Outlier detection with several methods.

../_images/plot_robust_vs_empirical_covariance.png

Robust vs Empirical covariance estimate

../_images/plot_sparse_cov.png

Sparse inverse covariance estimation

Dataset examples¶

Examples concerning the sklearn.datasets package.

../_images/plot_digits_last_image.png

The Digit Dataset

../_images/plot_iris_dataset.png

The Iris Dataset

../_images/plot_random_dataset.png

Plot randomly generated classification dataset

Tutorial exercises¶

Exercises for the tutorials

../_images/plot_cv_diabetes.png

Cross-validation on diabetes Dataset Exercise

../_images/plot_cv_digits.png

Cross-validation on Digits Dataset Exercise

../_images/plot_digits_classification_exercise.png

Digits Classification Exercise

../_images/plot_iris_exercise.png

Gaussian Process for Machine Learning¶

Examples concerning the sklearn.gaussian_process package.

../_images/plot_gp_probabilistic_classification_after_regression.png

Gaussian Processes classification example: exploiting the probabilistic output

../_images/plot_gp_regression.png

Gaussian Processes regression: basic introductory example

../_images/gp_diabetes_dataset.png

Gaussian Processes regression: goodness-of-fit on the ‘diabetes’ dataset

Generalized Linear Models¶

Examples concerning the sklearn.linear_model package.

../_images/plot_ard.png

Automatic Relevance Determination Regression (ARD)

../_images/plot_bayesian_ridge.png

Bayesian Ridge Regression

../_images/plot_iris_logistic.png

Logistic Regression 3-class Classifier

../_images/plot_lasso_and_elasticnet.png

Lasso and Elastic Net for Sparse Signals

../_images/plot_lasso_coordinate_descent_path.png

Lasso and Elastic Net

../_images/plot_lasso_lars.png

Lasso path using LARS

../_images/plot_lasso_model_selection.png

Lasso model selection: Cross-Validation / AIC / BIC

../_images/plot_logistic.png

Logit function

../_images/plot_logistic_l1_l2_sparsity.png

L1 Penalty and Sparsity in Logistic Regression

../_images/plot_logistic_path.png

Path with L1- Logistic Regression

../_images/plot_multi_task_lasso_support.png

Joint feature selection with multi-task Lasso

../_images/plot_ols.png

Linear Regression Example

../_images/plot_ols_3d.png

Sparsity Example: Fitting only features 1 and 2

../_images/plot_ols_ridge_variance.png

Ordinary Least Squares and Ridge Regression Variance

../_images/plot_omp.png

Orthogonal Matching Pursuit

../_images/plot_polynomial_interpolation.png

Polynomial interpolation

../_images/plot_ridge_path.png

Plot Ridge coefficients as a function of the regularization

../_images/plot_sgd_comparison.png

Comparing various online solvers

../_images/plot_sgd_iris.png

Plot multi-class SGD on the iris dataset

../_images/plot_sgd_loss_functions.png

SGD: Convex Loss Functions

../_images/plot_sgd_ols.png

Ordinary Least Squares with SGD

../_images/plot_sgd_penalties.png

SGD: Penalties

../_images/plot_sgd_separating_hyperplane.png

SGD: Maximum margin separating hyperplane

../_images/plot_sgd_weighted_classes.png

SGD: Separating hyperplane with weighted classes

../_images/plot_sgd_weighted_samples.png

SGD: Weighted samples

../_images/plot_sparse_recovery.png

Sparse recovery: feature selection for sparse linear models

../_images/lasso_dense_vs_sparse_data.png

Lasso on dense and sparse data

Manifold learning¶

Examples concerning the sklearn.manifold package.

../_images/plot_compare_methods.png

Comparison of Manifold Learning methods

../_images/plot_lle_digits.png

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

../_images/plot_manifold_sphere.png

Manifold Learning methods on a severed sphere

../_images/plot_mds.png

Multi-dimensional scaling

../_images/plot_swissroll.png

Swiss Roll reduction with LLE

Gaussian Mixture Models¶

Examples concerning the sklearn.mixture package.

../_images/plot_gmm.png

Gaussian Mixture Model Ellipsoids

../_images/plot_gmm_classifier.png

GMM classification

../_images/plot_gmm_pdf.png

Density Estimation for a mixture of Gaussians

../_images/plot_gmm_selection.png

Gaussian Mixture Model Selection

../_images/plot_gmm_sin.png

Gaussian Mixture Model Sine Curve

Nearest Neighbors¶

Examples concerning the sklearn.neighbors package.

../_images/plot_classification.png

Nearest Neighbors Classification

../_images/plot_nearest_centroid.png

Nearest Centroid Classification

../_images/plot_regression.png

Nearest Neighbors regression

Semi Supervised Classification¶

Examples concerning the sklearn.semi_supervised package.

../_images/plot_label_propagation_digits.png

Label Propagation digits: Demonstrating performance

../_images/plot_label_propagation_digits_active_learning.png

Label Propagation digits active learning

../_images/plot_label_propagation_structure.png

Label Propagation learning a complex structure

../_images/plot_label_propagation_versus_svm_iris.png

Decision boundary of label propagation versus SVM on the Iris dataset

Decision Trees¶

Examples concerning the sklearn.tree package.

../_images/plot_iris1.png

Plot the decision surface of a decision tree on the iris dataset

../_images/plot_tree_regression.png

Decision Tree Regression

../_images/plot_tree_regression_multioutput.png

Multi-output Decision Tree Regression