我是一名机器学习的初学者，正在通过Kaggle比赛学习。我从泰坦尼克号比赛开始，现在正试图使用scikit-learn的accuracy_score函数来测量我的预测准确度，但输出结果似乎不太合理。以下是我得到的输出：

[1. 0. 1. 0. 1. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1. 1. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1. 0. 1.]<function accuracy_score at 0x000001AA46EFBD90>

这是我的代码：

*imports have been omitted to avoid crowding    train_path = "C:\\Users\\Omar\\Downloads\\Titanic Data\\train.csv"    train_data = pd.read_csv(train_path)    train_data['Sex'] = pd.factorize(train_data.Sex)[0]    columns_of_interest = ['Survived','Pclass', 'Sex', 'Age']    filtered_titanic_data = train_data.dropna(axis=0)    x = filtered_titanic_data[columns_of_interest]    y = filtered_titanic_data.Survived    train_x, val_x, train_y, val_y = train_test_split(x, y, random_state=0)    titanic_model = DecisionTreeRegressor()    titanic_model.fit(train_x, train_y)    val_predictions = titanic_model.predict(val_x)    accuracy_score(val_y, val_predictions)    print(val_predictions)    print(accuracy_score)

回答：

你需要打印accuracy_score(val_y, val_predictions)行的结果。

例如，print(accuracy_score(val_y, val_predictions))