python中逻辑回归算法是什么？

from sklearn.linear_model import LogisticRegression

# 复习情况，格式为[时长，效率]

x_train=[(0,0),(7,0.9),(15,0.4),(13,0.9),(15,0.4),(16,0.4),(16,0.8),(15,0.7),(17,0.2),(7.5,0.8),(17,0.9),(18,0.1),(18,0.6),(18,0.8)]

y_train=[0,0,0,1,0,0,1,1,0,1,1,0,1,1] #0考不上，1考得上

# 创建并训练逻辑回归模型

reg=LogisticRegression()

reg.fit(x_train,y_train)

# 测试模型

x_test=[(3,0.1),(8,0.3),(7,0.2),(4,0.2),(4,0.4)]

y_test=[0,0,0,0,0]

score=reg.score(x_test,y_test)

# 预测并输出预测结果

learning=[(16,0.9)]

result=reg.predict_proba(learning)

msg='''模型得分：{0}

复习时长为：{1[0]},效率为：{1[1]}

您考不上的概率为：{2[0]}

您考的上的概率为：{2[1]}

总和判断，您会：{3}'''.format(score,learning[0],result[0],'考不上'if result[0][0]>0.5 else "考得上")

print(msg)