cvgraph |

Display a graph of the cross-validation objective against the lambda path.

This view is only available for equations estimated with elastic net, ridge regression, Lasso, and variable selection using Lasso.

Show a graph of the cross-validation objective for each value of lambda, along with bars representing +/– one standard deviation of the mean (for cross-validation methods that produce multiple training samples for each lambda).

A vertical line will be included to identify the selected optimal lambda.

Syntax

eq_name.cvgraph(options)

Options

p | Print output. |

Examples

Consider the estimated elastic net equation

equation my_eq.enet(xtrans=none, lambdaratio=.0001, cvseed=513255899) lpsa c lcavol_s lweight_s age_s lbph_s svi_s lcp_s gleason_s pgg45_s

Then the command

my_eq.cvgraph

displays a graph of the cross-validation measures of fit against the path of log lambda. The cross-validation selected optimal value of lambda is marked by a vertical line.

Cross-references

For further discussion, see
“Elastic Net and Lasso”

See also
Equation::lambdacoefs,
Equation::lambdapath.

The data underlying this graph are available via the data members @lambdafit, and @cvobjective.