- Thread starter Morena
- Start date

Side note, regularizing approaches usually entail:

-LASSO

-Ridge Regression

-Elastic Net

-Bayesian Modeling (with non-flat priors)

-etc., adding a weight for complexity, say just using any of the information criteria for model selection.

Side note, regularizing approaches usually entail:

-LASSO

-Ridge Regression

-Elastic Net

-Bayesian Modeling (with non-flat priors)

-etc., adding a weight for complexity, say just using any of the information criteria for model selection.

So, what are all other approaches that can be used to deal with sparsity?