Open cfkstat opened 3 years ago
My guess is to modify the scorecard class parameter Estimator, such as replacing the LogisticRegression with Glmnet, but I'm not sure this will work.
Hi @cfkstat,
Any class supporting .fit(), .predict() and predict_proba() is suitable to be used as an estimator. The Logistic regression in sklearn supports lasso and ridge regularization via parameter penalty
. The problem is that after fitting, there is no function to filter those variables with abs(coefficient) < threshold.
If I understood correctly, what you are proposing would require a function to retrieve estimator support, which it is currently missing.
How to develop a scorecard that uses lasso or ridge for variable screening to get a model that is more generalizable than a model with a full subset of variables?