[scikit-learn] No convergence warning in logistic regression
mail at sebastianraschka.com
Fri Aug 30 12:29:34 EDT 2019
I can recall seeing convergence warnings for scikit-learn's logistic regression model on datasets in the past as well. Which solver did you use for LogisticRegression in sklearn? If you haven't done so, have used the lbfgs solver? I.e.,
> On Aug 30, 2019, at 9:52 AM, Benoît Presles <benoit.presles at u-bourgogne.fr> wrote:
> Dear all,
> I compared the logistic regression of statsmodels (Logit) with the logistic regression of sklearn (LogisticRegression). As I do not do regularization, I use the fit method with statsmodels and set penalty='none' in sklearn. Most of the time, I have got the same results between the two packages.
> However, when data are correlated, it is not the case. In fact, I have got a very useful convergence warning with statsmodel (ConvergenceWarning: Maximum Likelihood optimization failed to converge) that I do not have with sklearn? Is it normal that I do not have any convergence warning with sklearn even if I put verbose=1? I guess sklearn did not converge either.
> Thanks for your help,
> Best regards,
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