Hi, I have got this error while running the code in the lecture, any advise?

I have faced the same issue, but in my case it was when I created a derived class from LinearRegression that contained some extra functionality to calculate the p-value. The missing part is initializing the base class during the initialization of the derived class, as I suspect the attribute "positive" has been added in a newer version. I have added: super().__init__(fit_intercept=fit_intercept, normalize=normalize, copy_X=copy_X, n_jobs=n_jobs) Here full code: class LinearRegression(linear_model.LinearRegression): """ LinearRegression class after sklearn's, but calculate t-statistics and p-values for model coefficients (betas). Additional attributes available after .fit() are tandp which are of the shape (y.shape[1], X.shape[1]) which is (n_features, n_coefs) This class sets the intercept to 0 by default, since usually we include it in X. """ # nothing changes in __init__ def __init__(self, fit_intercept=True, normalize=False, copy_X=True, n_jobs=1): super().__init__(fit_intercept=fit_intercept, normalize=normalize, copy_X=copy_X, n_jobs=n_jobs) self.fit_intercept = fit_intercept self.normalize = normalize self.copy_X = copy_X self.n_jobs = n_jobs

Following Fernando's answer, I solved the issue, adding 'positive' attribute: super().__init__(fit_intercept=fit_intercept, normalize=normalize, copy_X=copy_X, n_jobs=n_jobs, positive=False) self.positive = positive 'positive' = True, forces coefficient to be positive.

Follow this topic

Jaycus Goh

Last answered:

09 Sept 2021

Posted on:

20 Jun 2021

'LinearRegression' object has no attribute 'positive'

in Credit Risk Modeling in Python / LGD model: stage 2 – linear regression

2 answers ( 0 marked as helpful)

Fernando Garcia

Posted on:

30 Jun 2021

Felipe Saavedra

Posted on:

09 Sept 2021

'LinearRegression' object has no attribute 'positive'

Submit an answer