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- from flaml import AutoML
- from sklearn.datasets import fetch_california_housing
-
- # Initialize an AutoML instance
- automl = AutoML()
- # Specify automl goal and constraint
- automl_settings = {
- "time_budget": 1, # in seconds
- "metric": "r2",
- "task": "regression",
- "log_file_name": "test/california.log",
- }
- X_train, y_train = fetch_california_housing(return_X_y=True)
- # Train with labeled input data
- automl.fit(X_train=X_train, y_train=y_train, **automl_settings)
- print(automl.model)
- print(automl.model.estimator)
-
- print(automl.best_estimator)
- print(automl.best_config)
- print(automl.best_config_per_estimator)
-
- print(automl.best_config_train_time)
- print(automl.best_iteration)
- print(automl.best_loss)
- print(automl.time_to_find_best_model)
- print(automl.config_history)
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