* Replace all uses of deprecated function sklearn.datasets.load_boston * More renaming * Fix bad name * Update assertion * Fix n boosted rounds. * Avoid over regularization. * Rebase. * Avoid over regularization. * Whac-a-mole Co-authored-by: fis <jm.yuan@outlook.com>
26 lines
817 B
Python
26 lines
817 B
Python
import numpy as np
|
|
import xgboost as xgb
|
|
import pytest
|
|
|
|
try:
|
|
import shap
|
|
except ImportError:
|
|
shap = None
|
|
pass
|
|
|
|
pytestmark = pytest.mark.skipif(shap is None, reason="Requires shap package")
|
|
|
|
|
|
# Check integration is not broken from xgboost side
|
|
# Changes in binary format may cause problems
|
|
def test_with_shap():
|
|
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)
|