e in which only a relatively small number of parameters (or predictors) play an important role." (Hastie et al. 2016:1) aka a subset of the original variables. 

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# Lasso

Lambda `\(\lambda\)` is the regularization coefficient, or the degree to which the beta coefficients should be penalized.  

When `\(\lambda\)` is zero, ordinary least squares regression is performed. 

Alpha `\(\alpha\)` determines the type of model; 1 indicates lasso penalty, 0 indicates ridge penalty, and anything inbetween indicat