summary.gpe {pre} | R Documentation |
Summary method for a General Prediction Ensemble (gpe)
Description
summary.gpe
prints information about the generated ensemble
to the command line
Usage
## S3 method for class 'gpe'
summary(object, penalty.par.val = "lambda.1se", ...)
Arguments
object |
An object of class gpe .
|
penalty.par.val |
character or numeric. Value of the penalty parameter
\lambda to be employed for selecting the final ensemble. The default
"lambda.min" employs the \lambda value within 1 standard
error of the minimum cross-validated error. Alternatively,
"lambda.min" may be specified, to employ the \lambda value
with minimum cross-validated error, or a numeric value >0 may be
specified, with higher values yielding a sparser ensemble. To evaluate the
trade-off between accuracy and sparsity of the final ensemble, inspect
pre_object$glmnet.fit and plot(pre_object$glmnet.fit) .
|
... |
Further arguments to be passed to
coef.cv.glmnet .
|
Details
Note that the cv error is estimated with data that was also used
for learning rules and may be too optimistic.
Value
Prints information about the fitted ensemble.
See Also
gpe
, print.gpe
,
coef.gpe
, predict.gpe
[Package
pre version 1.0.7
Index]