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I've been attempting to fit this data by a Linear Regression, following a tutorial on bigdataexaminer. Everything was working fine up until this point. I imported LinearRegression from sklearn, and printed the number of coefficients just fine. This was the code before I attempted to grab the coefficients from the console.

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()

After I had all this set up I ran the following command, and it returned the proper output:

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

Number of coefficients: 13

However, now if I ever try to print this same line again, or use 'lm.coef_', it tells me coef_ isn't an attribute of LinearRegression, right after I JUST used it successfully, and I didn't touch any of the code before I tried it again.

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_'
ayhan
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Destroxia
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    Where do you call the fit method? With only the part you shared, len(lm.coef_) cannot print 13. – ayhan Jul 28 '16 at 20:27
  • I never called a fit method, but I can promise you, the first time I ran that line `print('Number of coefficients:', len(lm.coef_))` it definitely returned 13. I'm not sure if its a python 3 issue or whatnot, but it did print that the first time. – Destroxia Jul 28 '16 at 20:36
  • @Destroxia If you did not fit the function, how is there a coefficient??? – user1157751 Jul 28 '16 at 20:37
  • @Destroxia Essentially you are trying to solve m in y=mx+c, and the m is your coefficient. – user1157751 Jul 28 '16 at 20:39
  • What's there in between 68 and 70? I guess something like `runfile(...)`? – ayhan Jul 28 '16 at 20:41
  • Yes, I was just recompiling the code. – Destroxia Jul 28 '16 at 20:43

2 Answers2

33

The coef_ attribute is created when the fit() method is called. Before that, it will be undefined:

>>> 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_'

If we call fit(), the coefficients will be defined:

>>> 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])

My guess is that somehow you forgot to call fit() when you ran the problematic line.

jakevdp
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    Thank you, this seemed to fix the problem, although I'm not sure how it worked the first time without the fit. – Destroxia Jul 28 '16 at 20:43
0

I also got the same problem while dealing with linear regression the problem object has no attribute 'coef'. There are just slight changes in the syntax only.


linreg = LinearRegression()

linreg.fit(X,y) # fit the linesr model to the data

print(linreg.intercept_)

print(linreg.coef_)

I Hope this will help you Thanks

Rishabh Rathore
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