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How-to Guides

Task-oriented guides for common Sklearn-Wrap workflows. Each guide addresses a specific goal and assumes basic familiarity with the library.

Guide Description
Wrap a Class Turn any Python class into an sklearn estimator
Validate Parameters Add type and value constraints to wrapper parameters
Use YAML Configuration Build, save, and load estimators from YAML files
Use with GridSearchCV Run hyperparameter search on wrapped estimators
Nest Wrappers Compose wrappers inside other wrappers
Serialize Estimators Save and load fitted estimators with joblib
Test Your Wrapper Verify wrapper correctness and sklearn compatibility
Troubleshooting Common errors, their causes, and how to fix them
Advanced YAML Patterns YAML anchors, !include composition, multi-file configs
Contributing Contribute to the Sklearn-Wrap project