I read from literature that the following two methods can be used for feature selection prior to model development: 1. Correlation factor between target and feature variables (select those features that have correlation > threshold) 2. Lasso
Which of the above two methods is preferred?
In one of the exercises I did, Lasso retained some features which have a lower correlation than the features it dropped. In other words, the above two methods didn't result in the same set of features selected. How do we explain this?