following discussions from 1 and 2 try to speed-up how shap values are calculated. Using
shap.TreeExplainer from Shap library it takes 1.5 hours to process a dataframe of shape 50M rows and 10 columns.
Tested with limited success
deval = xgb.DMatrix(X_eval, label=y_eval)
shap_values = clf.get_booster().predict(deval, pred_contribs=True)
Any help would be greatly appreciated.