Elastic net regression models are controlled by two parameters, lambda, a measure of shrinkage, and alpha, a compromise between ridge and lasso regression. glmnet provides tools for selecting lambda via cross validation but no automated methods for selection of alpha. Elastic Net SearcheR automate the selection of both lambda and alpha.
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