objective_functon_optuna.py

def objective(trial):
    # Define the search space
    criterions = trial.suggest_categorical('criterion', ['gini', 'entropy'])
    max_depths = trial.suggest_int('max_depth', 1, 9, 1)
    n_estimators = trial.suggest_int('n_estimators', 100, 1000, 100)

    clf = sklearn.ensemble.RandomForestClassifier(n_estimators=n_estimators,
                                 criterion=criterions,
                                 max_depth=max_depths,
                                 n_jobs=-1)
                                 
    score = cross_val_score(clf, X_scaled, y, scoring="accuracy").mean()

    return score