= Lasso (statistics)
{wiki=Lasso_(statistics)}
Lasso, which stands for "Least Absolute Shrinkage and Selection Operator," is a statistical method used primarily in regression analysis. It is particularly useful for feature selection and regularization when dealing with a large number of predictors in a regression model. Here's an overview of its key characteristics: 1. **Regularization**: Lasso adds a penalty term to the ordinary least squares (OLS) regression cost function. This penalty is proportional to the absolute values of the coefficients of the predictors.
Back to article page
