tests.test_issues.test_issue_29.test_issue_29()   A
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Total Lines 29
Code Lines 20

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eloc 20
dl 0
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rs 9.4
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"""Test module for issue #29 reproduction."""
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from sklearn.datasets import load_diabetes
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from sklearn.model_selection import cross_val_score
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from sklearn.tree import DecisionTreeRegressor
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from hyperactive import Hyperactive
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def test_issue_29():
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    """Test issue 29 - accessing optimizer attributes during optimization."""
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    data = load_diabetes()
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    X, y = data.data, data.target
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    def model(para):
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        dtr = DecisionTreeRegressor(
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            min_samples_split=para["min_samples_split"],
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            max_depth=para["max_depth"],
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        )
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        scores = cross_val_score(dtr, X, y, cv=3)
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        print(
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            "Iteration:",
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            para.optimizer.nth_iter,
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            " Best score",
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            para.optimizer.best_score,
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        )
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        return scores.mean()
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    search_space = {
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        "min_samples_split": list(range(2, 12)),
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        "max_depth": list(range(2, 12)),
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    }
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    hyper = Hyperactive()
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    hyper.add_search(model, search_space, n_iter=20)
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    hyper.run()
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