Examples#
This is the gallery of examples that showcase how scikit-learn can be used. Some examples demonstrate the use of the API in general and some demonstrate specific applications in tutorial form. Also check out our user guide for more detailed illustrations.
Release Highlights#
These examples illustrate the main features of the releases of scikit-learn.
Biclustering#
Examples concerning biclustering techniques.
Calibration#
Examples illustrating the calibration of predicted probabilities of classifiers.
Classification#
General examples about classification algorithms.
Clustering#
Examples concerning the sklearn.cluster module.
Covariance estimation#
Examples concerning the sklearn.covariance module.
Cross decomposition#
Examples concerning the sklearn.cross_decomposition module.
Dataset examples#
Examples concerning the sklearn.datasets module.
Decision Trees#
Examples concerning the sklearn.tree module.
Decomposition#
Examples concerning the sklearn.decomposition module.
sphx_glr_auto_examples_decomposition_plot_ica_vs_pca.py
Developing Estimators#
Examples concerning the development of Custom Estimator.
Ensemble methods#
Examples concerning the sklearn.ensemble module.
sphx_glr_auto_examples_ensemble_plot_gradient_boosting_regularization.py
Examples based on real world datasets#
Applications to real world problems with some medium sized datasets or interactive user interface.
Feature Selection#
Examples concerning the sklearn.feature_selection module.
Gaussian Mixture Models#
Examples concerning the sklearn.mixture module.
Gaussian Process for Machine Learning#
Examples concerning the sklearn.gaussian_process module.
Generalized Linear Models#
Examples concerning the sklearn.linear_model module.
Inspection#
Examples related to the sklearn.inspection module.
Kernel Approximation#
Examples concerning the sklearn.kernel_approximation module.
Manifold learning#
Examples concerning the sklearn.manifold module.
Miscellaneous#
Miscellaneous and introductory examples for scikit-learn.
Missing Value Imputation#
Examples concerning the sklearn.impute module.
Model Selection#
Examples related to the sklearn.model_selection module.
sphx_glr_auto_examples_model_selection_plot_successive_halving_iterations.py
Multiclass methods#
Examples concerning the sklearn.multiclass module.
Multioutput methods#
Examples concerning the sklearn.multioutput module.
Nearest Neighbors#
Examples concerning the sklearn.neighbors module.
Neural Networks#
Examples concerning the sklearn.neural_network module.
Pipelines and composite estimators#
Examples of how to compose transformers and pipelines from other estimators. See the User Guide.
Preprocessing#
Examples concerning the sklearn.preprocessing module.
Semi Supervised Classification#
Examples concerning the sklearn.semi_supervised module.
Support Vector Machines#
Examples concerning the sklearn.svm module.
Tutorial exercises#
Exercises for the tutorials
sphx_glr_auto_examples_exercises_plot_iris_exercise.py
Working with text documents#
Examples concerning the sklearn.feature_extraction.text module.
