!!! Overview
[{$pagename}] ([LASSO]) is a shrinkage and selection method for [Linear Regression]. 

[{$pagename}] minimizes the usual [Residual Sum of Squares] ([RSS]), with a bound on the sum of the absolute values of the coefficients. 

[{$pagename}] has connections to soft-thresholding of wavelet coefficients, forward stagewise regression, and boosting methods. 

!! [{$pagename}] [Regularization]
[{$pagename}] is used as a [Regularization] method to also minimize the absolute sum of the coefficients (called L1 [Regularization]).

!! More Information
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