python-3.x - 总是得到1的精度如何解决？

Question

我正在尝试对我的数据集应用逻辑回归，但它的准确度为 1

df = pd.read_csv("train.csv", header=0)

df = df[["PassengerId", "Survived", "Sex", "Age", "Embarked"]]
df.dropna(inplace=True)

X = df[["Sex", "Age"]]
X_train = np.array(X)

Y = df["Survived"]
Y_train = np.array(Y)

clf = LogisticRegression()
clf.fit(X_train, Y_train)

df1 = pd.read_csv("test.csv", header=0)
df1 = df1[["PassengerId", "Survived", "Sex", "Age", "Embarked"]]
df1.dropna(inplace=True)

X = df1[["Sex", "Age"]]
X_test = np.array(X)

Y = df1["Survived"]
Y_test = np.array(Y)
X_test = X_test.astype(float)
Y_test = Y_test.astype(float)
#to convert string data to float
accuracy = clf.score(X_test, Y_test)
print("Accuracy = ", accuracy)

我希望输出在 0 和 1 之间，但总是得到 1.0

标签： python-3.xscikit-learnclassificationlogistic-regression