Overview#

Least Absolute Shrinkage and Selection Operator (LASSO) is a shrinkage and selection method for Linear Regression.

Least Absolute Shrinkage and Selection Operator minimizes the usual Residual Sum of Squares (RSS), with a bound on the sum of the absolute values of the coefficients.

Least Absolute Shrinkage and Selection Operator has connections to soft-thresholding of wavelet coefficients, forward stagewise regression, and boosting methods.

Least Absolute Shrinkage and Selection Operator Regularization#

Least Absolute Shrinkage and Selection Operator is used as a Regularization method to also minimize the absolute sum of the coefficients (called L1 Regularization).

More Information#

There might be more information for this subject on one of the following:

• LASSO
• Machine Learning Algorithms