AutoML

Automated hyperparameter tuning and model selection.

Hyperparameter Tuning

Automatically tune model hyperparameters:

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-- AutoML hyperparameter tuning
SELECT automl_tune_hyperparameters(
    'training_table',
    'features',
    'label',
    'random_forest',  -- model type
    '{"n_trees": [50, 100, 200], "max_depth": [5, 10, 15]}'::jsonb
);

Model Selection

Automatically select best model:

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-- AutoML model selection
SELECT automl_select_model(
    'training_table',
    'features',
    'label',
    ARRAY['random_forest', 'xgboost', 'svm']  -- candidate models
) AS best_model;

AutoML Training

Train with automatic optimization:

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-- Train with AutoML
SELECT automl_train(
    'training_table',
    'features',
    'label',
    'classification'
);

Learn More

For detailed documentation on AutoML, hyperparameter search strategies, model selection criteria, and optimization techniques, visit:

AutoML Documentation

Related Topics

• Classification - Classification algorithms
• Random Forest - Random Forest models