Originally posted by toneart
Roger-
Here is one definition of Lasso on Google. Had I put this up for your guess, I am pretty sure you would be wrong (let's face it, I am a sore loser):
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.
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