#define a function for random forest regressor
from sklearn.ensemble import RandomForestRegressor
def RandomForestRegressorModel(X,y):
    X_train, X_test, y_train, y_test = train_test_split(X, y,random_state=42, test_size=0.3)
    rf = RandomForestRegressor(random_state=42)
    rf.fit(X_train, y_train)
    y_pred = rf.predict(X_test)
    print(print_accuracy_report(y_test, y_pred, X_test, rf))
    return rf
randomForestModel = RandomForestRegressorModel(X,y)