summary.gpe: Summary method for a General Prediction Ensemble (gpe)

View source: R/gpe_miscs.R

summary.gpeR 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 λ to be employed for selecting the final ensemble. The default "lambda.min" employs the λ value within 1 standard error of the minimum cross-validated error. Alternatively, "lambda.min" may be specified, to employ the λ 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


pre documentation built on June 11, 2022, 1:10 a.m.