cvshrink
Cross-validate pruning and regularization of regression ensemble
Description
returns an vals
= cvshrink(ens
)L
-by-T
matrix with cross-validated
values of the mean squared error. L
is the number of
Lambda
values in the ens.Regularization
structure. T
is the number of
Threshold
values on weak learner weights. If
ens
does not have a Regularization
property containing values specified by the regularize
function, set the Lambda
name-value
argument.
[___]
= cvshrink(
specifies additional options using one or more name-value arguments. For example,
you can specify the number of folds to use, the fraction of data to use for holdout
validation, and lower cutoffs on weights for weak learners.ens
,Name=Value
)
Examples
Input Arguments
Name-Value Arguments
Output Arguments
Extended Capabilities
Version History
Introduced in R2011a
See Also
regularize
| shrink
| RegressionEnsemble
| RegressionBaggedEnsemble
| fitrensemble