Is there a parameter to set the grouped data to only random intercept?

[phoenix-hy]

Hello. Thank you so much for providing this package.

I want to use gpboost to combine the mixed model for binary classification, but I just want my grouped data to be only random intercept, not random slope. Is there a parameter that can be set for this? below is my code with Python：

data_train = gpb.Dataset(x_train, y_train) gp_model = gpb.GPModel(group_data=group_train, likelihood=likelihood) gp_model.set_optim_params(params={"optimizer_cov": "nelder_mead"}) bst = gpb.train(train_set=data_train, gp_model=gp_model, num_boost_round=5000, params=params)

Is there a parameter that can be set in gpb.GPModel or any where?

[fabsig]

Thank you for your feedback.

Only a grouped random intercept and no random slope is the default. The way you run your code, you only have a random intercept effect.

[phoenix-hy]

@fabsig Thank you very much！