How to get p-value and confident interval in LogisticRegression with sklearn?
One way to get confidence intervals is to bootstrap your data, say, $B$ times and fit logistic regression models $m_i$ to the dataset $B_i$ for $i = 1, 2, ..., B$. This gives you a distribution for the parameters you are estimating, from which you can find the confidence intervals.