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)


summary.gpe prints information about the generated ensemble to the command line


## S3 method for class 'gpe'
summary(object, penalty.par.val = "lambda.1se", ...)



An object of class gpe.


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$ and plot(pre_object$


Further arguments to be passed to


Note that the cv error is estimated with data that was also used for learning rules and may be too optimistic.


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.