I'm just doing some interview preparation for a data science interview and this question came up.
I'm familiar with general feature selection methods such as best subset selection, forward stepwise, backward stepwise, and lasso regression to help select most important feature. However, these methods work in general, and I'm not sure if they work particularly well with sparse matrices and/or if there is something better.
Are there other considerations in particular for sparse matrices?
Thank you in advance for your help!