Product & software
scikit-learn
scikit-learn provides Python tools for conventional machine-learning workflows such as classification, regression, clustering, and preprocessing.
At a glance
- Primary focus
- Predictive modeling in Python
- Category
- machine learning
Overview
scikit-learn provides Python tools for conventional machine-learning workflows such as classification, regression, clustering, and preprocessing. Its estimator interface gives many algorithms a consistent way to fit data and produce results.
How it is used
Preprocessing and models can be combined in pipelines. Model-selection tools help compare configurations, while metrics evaluate predictions on data that was not used to fit the model.
A useful distinction
Data leakage can make evaluation misleading. Keep fitting operations within the training workflow and separate held-out evaluation data when measuring how well a model generalizes.
Sources and review
MOOR's explanatory text is supported by the following source links.
- scikit-learn: official overview — scikit-learn
- scikit-learn: documentation and further reading — scikit-learn