.. _method-polynomial_chaos-expansion_order-collocation_points-least_absolute_shrinkage: """""""""""""""""""""""" least_absolute_shrinkage """""""""""""""""""""""" Compute the coefficients of a polynomial expansion by using the LASSO problem. .. toctree:: :hidden: :maxdepth: 1 method-polynomial_chaos-expansion_order-collocation_points-least_absolute_shrinkage-noise_tolerance method-polynomial_chaos-expansion_order-collocation_points-least_absolute_shrinkage-l2_penalty **Specification** - *Alias:* lasso - *Arguments:* None **Child Keywords:** +-------------------------+--------------------+---------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+=====================+=============================================+ | Optional | `noise_tolerance`__ | The noise tolerance used when performing | | | | cross validation in the presence of noise | | | | or truncation errors. | +----------------------------------------------+---------------------+---------------------------------------------+ | Optional | `l2_penalty`__ | The :math:`l_2` pentalty used when | | | | performing compressed sensing with elastic | | | | net. | +----------------------------------------------+---------------------+---------------------------------------------+ .. __: method-polynomial_chaos-expansion_order-collocation_points-least_absolute_shrinkage-noise_tolerance.html __ method-polynomial_chaos-expansion_order-collocation_points-least_absolute_shrinkage-l2_penalty.html **Description** Compute the coefficients of a polynomial expansion by using the LASSO problem.