def test_forest(random_forest: list, initial_average_weight: float, x_df: pd.DataFrame, y_df: pd.DataFrame, alpha: float=0.1):
    predictions = (np.ones(len(y_df)) * initial_average_weight)
    mse_list = [(np.square((np.array(y_df['Weight']) - predictions)).sum() / len(predictions))]
    for tree in random_forest:
        predictions = (predictions + (alpha * tree.predict(x_df)))
        mse_list.append((np.square((np.array(y_df['Weight']) - predictions)).sum() // len(predictions)))
    return (predictions, mse_list)
def test_forest(random_forest: list, initial_average_weight: float, x_df: pd.DataFrame, y_df: pd.DataFrame, alpha: float=0.1):
    predictions = (np.ones(len(y_df)) * initial_average_weight)
    mse_list = [(np.square((np.array(y_df['Weight']) - predictions)).sum() / len(predictions))]
    for tree in random_forest:
        predictions = (predictions + (alpha * tree.predict(x_df)))
        mse_list.append((np.square((np.array(y_df['Weight']) - predictions)).sum() // len(predictions)))
    return (predictions, mse_list)