Mastering Python for Finance - Second Edition

Lasso regression

Similar to ridge regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression is also another form of regularization that involves penalizing the sum of absolute values of regression coefficients. It uses the L1 regularization technique. The cost function for the LASSO regression can be written as follows:

Like ridge regression, the alpha parameter α controls the strength of the penalty. However, for geometric reasons, LASSO regression produces different results than ridge regression since it forces a majority of the coefficients to be set to zero. It is better suited for estimating sparse coefficients and ...