''LinearRegression' object has no attribute 'summary'

from sklearn.linear_model import LinearRegression

lr= LinearRegression()

X=[[1.1,1.3,1.5]]
y=[[39343,46205,37731]]

lr.fit(X, y)

lr.summary()


AttributeError Traceback (most recent call last) in ----> 1 lr.summary()

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



Solution 1:[1]

The method summary(), simply does not exist under the name lr, if you are trying to access the coefficients you can use :

reg.coef_

other than that, you would be better off checking the docs : sklearn.linear_model.LinearRegression docs

or you can instantly check what names you can access under lr using :

dir(lr)

or read the help docs using :

help(lr)

Solution 2:[2]

I have this problem all the time. It's because you need to use statsmodel's Ordinary Least Square function (sm.OLS(y,x,data=data_frame)) before fitting the model. You should probably add a constant to the x axis as well:

from sklearn.linear_model import LinearRegression
import statsmodels.api as sm

lr= LinearRegression()

X=[[1.1,1.3,1.5]]
y=[[39343,46205,37731]]
X = sm.add_constant(X)

model = sm.OLS(y,X)
fitted_model = model.fit()
fitted_model.summary()

Solution 3:[3]

I was confused b/w R's regression and python's.

and yes if u want to see the similar summary report in python then , statsmodels' Ordinary Least Square is the way to do it.

Sources

This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.

Source: Stack Overflow

Solution Source
Solution 1 Pixel_teK
Solution 2 Franch Dressing
Solution 3 aditya nagdiya