sklearn.utils (original) (raw)

Various utilities to help with development.

Developer guide. See the Utilities for Developers section for further details.

Input and parameter validation#

Functions to validate input and parameters within scikit-learn estimators.

Meta-estimators#

Utilities for meta-estimators.

Weight handling based on class labels#

Utilities for handling weights based on class labels.

Dealing with multiclass target in classifiers#

Utilities to handle multiclass/multioutput target in classifiers.

Optimal mathematical operations#

Utilities to perform optimal mathematical operations in scikit-learn.

Working with sparse matrices and arrays#

A collection of utilities to work with sparse matrices and arrays.

Utilities to work with sparse matrices and arrays written in Cython.

Working with graphs#

Graph utilities and algorithms.

Random sampling#

Utilities for random sampling.

Auxiliary functions that operate on arrays#

A small collection of auxiliary functions that operate on arrays.

Metadata routing#

Utilities to route metadata within scikit-learn estimators.

User guide. See the Metadata Routing section for further details.

Discovering scikit-learn objects#

Utilities to discover scikit-learn objects.

API compatibility checkers#

Various utilities to check the compatibility of estimators with scikit-learn API.

Parallel computing#

Customizations of joblib and threadpoolctl tools for scikit-learn usage.