* Accept array interface for csr and array. * Accept an optional proxy dmatrix for metainfo. This constructs an explicit `_ProxyDMatrix` type in Python. * Remove unused doc. * Add strict output.
25 lines
740 B
Python
25 lines
740 B
Python
import numpy as np
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import xgboost as xgb
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import pytest
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try:
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import shap
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except ImportError:
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shap = None
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pass
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pytestmark = pytest.mark.skipif(shap is None, reason="Requires shap package")
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# Check integration is not broken from xgboost side
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# Changes in binary format may cause problems
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def test_with_shap():
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X, y = shap.datasets.boston()
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dtrain = xgb.DMatrix(X, label=y)
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model = xgb.train({"learning_rate": 0.01}, dtrain, 10)
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explainer = shap.TreeExplainer(model)
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shap_values = explainer.shap_values(X)
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margin = model.predict(dtrain, output_margin=True)
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assert np.allclose(np.sum(shap_values, axis=len(shap_values.shape) - 1),
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margin - explainer.expected_value, 1e-3, 1e-3)
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