summary.gpe
prints information about the generated ensemble
to the command line
# S3 method for gpe
summary(object, penalty.par.val = "lambda.1se", ...)
Prints information about the fitted ensemble.
An object of class gpe
.
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
.
Note that the cv error is estimated with data that was also used for learning rules and may be too optimistic.
gpe
, print.gpe
,
coef.gpe
, predict.gpe