R: Summary method for a General Prediction Ensemble (gpe)

summary.gpe {pre}

R 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", ...)

`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`.

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.