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'

2

3 Answers

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)

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()

1

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.

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