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. … Least Absolute Shrinkage and Selection Operator (LASSO)
If you did not already know: “Least Absolute Shrinkage and Selection Operator (LASSO)”
27 Tuesday Jan 2015
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