Scikit-learn LinearRegression：如何解决错误“ fit（）缺少1个必需的位置参数：'y'”？

Question

我的代码：

import pandas as pd
from sklearn.Linear_model import LinearRegression as lr
df = pd.DataFrame({"Match Score":[95,85,80,70,60], "Statistic score":[85,95,70,65,70]})
x =df[["Match Score"]]
y =df["Statistic score"]
lr.fit(x,y)

错误详细信息：

TypeError                                 Traceback (most recent call last)
<ipython-input-19-e644bf405118> in <module>
----> 1 lr.fit(x,y)

TypeError: fit() missing 1 required positional argument: 'y'

Answer 1

您必须首先实例化LinearRegression估计器。

my_lr = lr().fit(x,y)

您的导入语句中也有错字，它是sklearn.linear_model加上一个小l。

Answer 2

import pandas as pd
from sklearn.linear_model import LinearRegression

df = pd.DataFrame({"Match Score": [95,85,80,70,60], "Statistic score": [85,95,70,65,70]})

x = df[["Match Score"]]
y = df["Statistic score"]

m = LinearRegression().fit(x, y)

print(m.intercept_) # intercept
26.780821917808225

print(m.coef_) # slope
[0.64383562]