I am trying to apply the lasso or ridge regression to my data set for the feature selection, but different random seeds produce different models. What is a good or universal way to obtain the final model?
- Fix a seed, OR
- combine models from different seeds (if so, then how should I combine them?), OR
- compare models from several different seeds and find a kind of representative model?
Any comments or references will be really appreciated!