【代码模版】python实现逻辑回归预测及评估的通用代码

from sklearn.linear_model import LogisticRegression
# 实例化模型
lr = LogisticRegression(C=c_value, penalty='l1', solver='liblinear')
# 训练模型
lr.fit(x_train, y_train.values.ravel())
# 模型预测
y_predict = lr.predict(x_test)
# 模型评估
from sklearn.metrics import '此处填写适当的评估方法X'
score = X(y_test, y_predict)
print(score)