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

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Jaycus Goh

Last answered:

June 30, 2021

Posted on:

June 20, 2021

'LinearRegression' object has no attribute 'positive'

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

1 answers ( 0 marked as helpful)

Fernando Garcia

Posted on:

June 30, 2021

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