import numpy as np
from sklearn.ensemble improt RandomForestRegressor

# Function mapping hyperparameters to a real-valued scpre
def objective(hyperparameters):

    # Machine learning model
    rf = RandomForestRegressor(**hyperparameters)

    # Training
    rf.fit(X_train, y_train)

    # Making predictions and evaluating
    predictions = rf.predict(X_valid)
    rmse = np.sqrt(np.mean(np.square(prediction - y_valid)))

    return rmse