I have a dataset with a lot of categorical variables and a binary target variable and I want to put it to an svm. I converted the categorical variables to dummy variables and since my observations are a lot less than the variables I want to perform feature selection. Since I have categorical variables converted to dummy variables I understand that I cant use simple lasso since it will drop part of the dummy variables.
I'm searching to find a package to implement group lasso on python with a binary target but I cant find any.
I found Adaptive Sparse Group Lasso (asgl) but as far as I understand it doesn't support binary target variables.
I also found group lasso which does sparse group lasso and supports logistic regression. As far as I understand sparse lasso does a combination between group lasso and lasso. I tried using it with parameters values to group_reg=0, or l1_reg=0 hopping that it would just do group lasso but it keeps droping part of the dummy variables in both cases.
My question is. How do you do group lasso with a binary target variable in python.
Thanks in advance.