Am working on a binary classification with 1000 rows and 28 columns.
I would wish to use an Auto-ML solution to try out different combinations of hyperparameters etc but the algo should only be
I don't wish to use other algorithms for the lack of interpretability.
So, I would like my auto-ML solution to stick to logistic regression and try out different values for hyperparameters. Of course, I might use fixed estimators like Decision trees, random forests etc as well
Is there any auto-ML solution that can use fixed estimator?
I read about
AutoML etc but they all try multiple algorithms and finally output the best one (which may not be logistic regression). How can I restrict my auto-ML solution to only use logistic regression?