summary.gpe prints information about the generated ensemble
to the command line
# S3 method for gpe
summary(object, penalty.par.val = "lambda.1se", ...)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).
Additional arguments, currently not used.
Prints information about the fitted ensemble.
Note that the cv error is estimated with data that was also used for learning rules and may be too optimistic.