AttributeError: LinearRegression object has no attribute 'coef_'

AttributeError: LinearRegression object has no attribute 'coef_'

我一直在尝试按照 bigdataexaminer 上的教程通过线性回归来拟合这些数据。直到此时一切都运行良好。我从 sklearn 导入了 LinearRegression,并打印出系数的数量就好了。这是我尝试从控制台获取系数之前的代码。

import numpy as np
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
import sklearn
from sklearn.datasets import load_boston
from sklearn.linear_model import LinearRegression

boston = load_boston()
bos = pd.DataFrame(boston.data)
bos.columns = boston.feature_names
bos['PRICE'] = boston.target

X = bos.drop('PRICE', axis = 1)

lm = LinearRegression()

完成所有这些设置后,我 运行 执行了以下命令,它返回了正确的输出:

In [68]: print('Number of coefficients:', len(lm.coef_)

Number of coefficients: 13

但是,现在如果我再次尝试打印同一行,或使用 'lm.coef_',它会告诉我 coef_ 不是 LinearRegression 的属性,就在我成功使用它之后,我没有在我再次尝试之前触摸任何代码。

In [70]: print('Number of coefficients:', len(lm.coef_))

Traceback (most recent call last):

 File "<ipython-input-70-5ad192630df3>", line 1, in <module>
print('Number of coefficients:', len(lm.coef_))

AttributeError: 'LinearRegression' object has no attribute 'coef_'

调用fit()方法时创建coef_属性。在此之前,它将是未定义的:

>>> import numpy as np
>>> import pandas as pd
>>> from sklearn.datasets import load_boston
>>> from sklearn.linear_model import LinearRegression

>>> boston = load_boston()

>>> lm = LinearRegression()
>>> lm.coef_
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-22-975676802622> in <module>()
      7 
      8 lm = LinearRegression()
----> 9 lm.coef_

AttributeError: 'LinearRegression' object has no attribute 'coef_'

如果我们调用fit(),系数将定义为:

>>> lm.fit(boston.data, boston.target)
>>> lm.coef_
array([ -1.07170557e-01,   4.63952195e-02,   2.08602395e-02,
         2.68856140e+00,  -1.77957587e+01,   3.80475246e+00,
         7.51061703e-04,  -1.47575880e+00,   3.05655038e-01,
        -1.23293463e-02,  -9.53463555e-01,   9.39251272e-03,
        -5.25466633e-01])

我的猜测是,当您 运行 有问题的行时,您以某种方式忘记了调用 fit()