nb.ipynb
import xgboost as xgb
import shap
import pandas as pd
data = pd.read_csv("data.csv")
X, y = data[features], data[[target]]
clf = xgb.XGBClassifier(tree_method="gpu_exact")
clf.fit(X, y)nb.ipynb
%%time
xgb_explainer = shap.TreeExplainer(clf,)
shap_values = xgb_explainer.shap_values(X)
Wall time: 21min 37snb.ipynb
%%time
booster = clf.get_booster()
shap_values = booster.predict(xgb.DMatrix(X),
pred_contribs=True)
# Remove the bias column
shap_values = shap_values[:, :-1]
Wall time: 1.4 s