4bbf062ed3
* Remove nthread, seed, silent. Add tree_method, gpu_id, num_parallel_tree. Fix #4909. * Check data shape. Fix #4896. * Check element of eval_set is tuple. Fix #4875 * Add doc for random_state with hogwild. Fixes #4919
32 lines
999 B
Python
32 lines
999 B
Python
import xgboost as xgb
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import pytest
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import sys
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import numpy as np
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sys.path.append("tests/python")
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import testing as tm
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pytestmark = pytest.mark.skipif(**tm.no_sklearn())
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rng = np.random.RandomState(1994)
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def test_gpu_binary_classification():
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from sklearn.datasets import load_digits
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from sklearn.model_selection import KFold
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digits = load_digits(2)
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y = digits['target']
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X = digits['data']
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kf = KFold(n_splits=2, shuffle=True, random_state=rng)
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for cls in (xgb.XGBClassifier, xgb.XGBRFClassifier):
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for train_index, test_index in kf.split(X, y):
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xgb_model = cls(
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random_state=42, tree_method='gpu_hist',
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n_estimators=4, gpu_id='0').fit(X[train_index], y[train_index])
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preds = xgb_model.predict(X[test_index])
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labels = y[test_index]
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err = sum(1 for i in range(len(preds))
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if int(preds[i] > 0.5) != labels[i]) / float(len(preds))
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assert err < 0.1
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