>>> mif = IsolationForest(massive=True, random_state=2, group_params={'Group_1': {'n_estimators':50})

>>> mif.fit(data=df, key="ID", group_key="GROUP_ID", features=['F1', 'F2'])

>>> res, err = mif.predict(data=df_predict, key="ID", group_key="GROUP_ID", features=['F1', 'F2'], group_params={'Group_1': {'contamination':0.2})