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* lint * bump ver * bump ver * fixed circular import --------- Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com>
15 lines
529 B
Python
15 lines
529 B
Python
from flaml.automl.data import load_openml_dataset
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from flaml.automl.ml import sklearn_metric_loss_score
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from flaml.default import LGBMRegressor
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X_train, X_test, y_train, y_test = load_openml_dataset(dataset_id=537, data_dir="./")
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lgbm = LGBMRegressor()
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hyperparams, estimator_name, X_transformed, y_transformed = lgbm.suggest_hyperparams(X_train, y_train)
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print(hyperparams)
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lgbm.fit(X_train, y_train)
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y_pred = lgbm.predict(X_test)
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print("flamlized lgbm r2 =", 1 - sklearn_metric_loss_score("r2", y_pred, y_test))
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print(lgbm)
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