编辑代码

# 假设data是一个包含'预估薪资'和'是否会购买'列的DataFrame
x = data['预估薪资']
y = data['是否会购买']

from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=2020)

# 将数据reshape为2D数组(因为sklearn要求特征矩阵是2D的)
x_train = x_train.values.reshape(-1, 1)
x_test = x_test.values.reshape(-1, 1)

from sklearn.linear_model import LogisticRegression
model = LogisticRegression()
model.fit(x_train, y_train)

# 计算模型在测试集上的准确率
acc = model.score(x_test, y_test)
print( acc)

# 预测测试集结果
y_test_pred = model.predict(x_test)
print(y_test_pred)