I am a little confused about this. I've read a lot but I really need some support from others who have knowledge about LARS and LASSO. Thanks in advance to all who are willing to contribute.
I found the link below provided a very nice thumbnail explanation -
LARS represents an efficient algorithm to calculate the entire family of LASSO solutions - that is for the entire range of bound parameters (s constraint) for |beta|
I've played around a little with the R package glmnet for fitting these models- but have been focusing more on RandomForest models in my work, though Andrew Gelman had a very interesting recent blog post on practical advantages of the LASSO approach that is making me want to use it more...