Defining the parameters

parameters.py

def objective(trial):
    # Categorical parameter
    optimizer = trial.suggest_categorical('rf_criterion', ['gini', 'entropy'])

    # Int parameter
    num_layers = trial.suggest_int("rf_n_estimators", 10, 1000)

    # Uniform parameter
    dropout_rate = trial.suggest_uniform('rf_min_weight_fraction_leaf', 0.0, 1.0)

    # Loguniform parameter
    learning_rate = trial.suggest_loguniform('rf_parameter_x', 1e-5, 1e-2)

    # Discrete-uniform parameter
    drop_path_rate = trial.suggest_discrete_uniform('rf_parameter_y', 0.0, 1.0, 0.1)