ML Assistance#

This section contains documentation for skore features that enhance the ML development process.

Get assistance when developing ML/DS projects#

These functions and classes build upon scikit-learn’s functionality.

`evaluate`(estimator, X, y, *[, splitter, ...])	Evaluate one or more estimators on the given data.
`train_test_split`(*arrays[, X, y, test_size, ...])	Perform train-test-split of data.
`TrainTestSplit`([test_size, train_size, ...])	Single train-test split implementing the cross-validation protocol.

Single Estimator Report#

skore.EstimatorReport provides comprehensive reporting capabilities for individual scikit-learn estimators, including metrics, visualizations, and evaluation tools.

Cross-validation Report#

skore.CrossValidationReport provides comprehensive capabilities for evaluating scikit-learn estimators by cross-validation, and reporting the results.

Comparison Report#

skore.ComparisonReport provides comprehensive capabilities for comparing skore.EstimatorReport or skore.CrossValidationReport instances, and reporting the results.

Visualization Displays#

A set of displays are available through the different reports. Find in this section the API of each display.