python - Scikit-Learn 准确度分数不显示准确度

Question

我是机器学习的初学者，我正在通过 Kaggle 比赛学习。我从泰坦尼克号竞赛开始，现在我尝试使用 scikit-learn accuracy_score 函数来测量我的预测的准确性，但输出并没有真正意义。这是我得到的输出:

[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)

Answer 1

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

例如打印(accuracy_score(val_y，val_predictions))