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import numpy as np
import pytest
import xgboost as xgb
try:
import shap
except Exception:
shap = None
pass
pytestmark = pytest.mark.skipif(shap is None, reason="Requires shap package")
# xgboost removed ntree_limit in 2.0, which breaks the SHAP package.
@pytest.mark.xfail
def test_with_shap() -> None:
from sklearn.datasets import fetch_california_housing
X, y = fetch_california_housing(return_X_y=True)
dtrain = xgb.DMatrix(X, label=y)
model = xgb.train({"learning_rate": 0.01}, dtrain, 10)
explainer = shap.TreeExplainer(model)
shap_values = explainer.shap_values(X)
margin = model.predict(dtrain, output_margin=True)
assert np.allclose(
np.sum(shap_values, axis=len(shap_values.shape) - 1),
margin - explainer.expected_value,
1e-3,
1e-3,
)
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