Примеры

Release Highlights

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

Бинарная кластеризация

Примеры из модуля sklearn.cluster.bicluster

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.

Ensemble methods

Examples concerning the sklearn.ensemble module.

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.

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

Working with text documents

Examples concerning the sklearn.feature_extraction.text module.