The Lasso Page
L1-constrained fitting |
The Lasso is a shrinkage and selection method for linear regression.
It minimizes the usual sum of squared errors, with a bound on the sum of the
absolute values of the coefficients. It has connections to soft-thresholding
of wavelet coefficients, forward stagewise regression, and boosting methods.
The glmnet package for fitting Lasso and elastic net models can be found on
CRAN .
Here is a MATLAB version .