~/miniconda3/lib/python3.8/site-packages/gpboost/engine.py in train(params, train_set, num_boost_round, gp_model, use_gp_model_for_validation, train_gp_model_cov_pars, valid_sets, valid_names, fobj, feval, init_model, feature_name, categorical_feature, early_stopping_rounds, evals_result, verbose_eval, learning_rates, keep_training_booster, callbacks)
276 # construct booster
277 try:
--> 278 booster = Booster(params=params, train_set=train_set, gp_model=gp_model)
279 if is_valid_contain_train:
280 booster.set_train_data_name(train_data_name)

~/miniconda3/lib/python3.8/site-packages/gpboost/basic.py in init(self, params, train_set, model_file, model_str, silent, gp_model)
2383 self.has_gp_model = True
2384 self.gp_model = gp_model
-> 2385 _safe_call(_LIB.LGBM_GPBoosterCreate(
2386 train_set.construct().handle,
2387 c_str(params_str),

~/miniconda3/lib/python3.8/site-packages/gpboost/basic.py in _safe_call(ret)
113 """
114 if ret != 0:
--> 115 raise GPBoostError(_LIB.LGBM_GetLastError().decode('utf-8'))
116
117

GPBoostError: The GPBoost algorithm can currently not be used for objective = quantile. If this is desired, contact the developer or open a GitHub issue.

It would be fantastic if quantile regression support could be added.