Testing hist_util (#5251)
* Rank tests * Remove categorical split specialisation * Extend tests to multiple features, switch to WQSketch * Add tests for SparseCuts * Add external memory quantile tests, fix some existing tests
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@@ -132,8 +132,8 @@ def run_suite(param, num_rounds=10, select_datasets=None, scale_features=False):
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"""
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datasets = [
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Dataset("Boston", get_boston, "reg:squarederror", "rmse"),
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Dataset("Digits", get_digits, "multi:softmax", "merror"),
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Dataset("Cancer", get_cancer, "binary:logistic", "error"),
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Dataset("Digits", get_digits, "multi:softmax", "mlogloss"),
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Dataset("Cancer", get_cancer, "binary:logistic", "logloss"),
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Dataset("Sparse regression", get_sparse, "reg:squarederror", "rmse"),
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Dataset("Sparse regression with weights", get_sparse_weights,
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"reg:squarederror", "rmse", has_weights=True),
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@@ -53,7 +53,7 @@ def assert_classification_result(results):
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r["param"]["objective"] != "reg:squarederror"]
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for res in classification_results:
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# Check accuracy is reasonable
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assert res["eval"][-1] < 0.5, (res["dataset"].name, res["eval"][-1])
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assert res["eval"][-1] < 2.0, (res["dataset"].name, res["eval"][-1])
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class TestLinear(unittest.TestCase):
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