R: print a cross-validated glmnet object

print.cv.glmnet {glmnet} | R Documentation

## print a cross-validated glmnet object

### Description

Print a summary of the results of cross-validation for a glmnet model.

### Usage

    ## S3 method for class 'cv.glmnet'
    print(x, digits = max(3, getOption("digits") - 3), ...)

### Arguments

`x` | fitted 'cv.glmnet' object
`digits` | significant digits in printout
`...` | additional print arguments

### Details

A summary of the cross-validated fit is produced, slightly different for a 'cv.relaxed' object than for a 'cv.glmnet' object. Note that a 'cv.relaxed' object inherits from class 'cv.glmnet', so by directly invoking `print.cv.glmnet(object)` will print the summary as if `relax=TRUE` had not been used.

### Author(s)

Jerome Friedman, Trevor Hastie and Rob Tibshirani
Maintainer: Trevor Hastie hastie@stanford.edu

### References

Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent
https://arxiv.org/abs/1707.08692
Hastie, T., Tibshirani, Robert, Tibshirani, Ryan (2019) Extended Comparisons of Best Subset Selection, Forward Stepwise Selection, and the Lasso

### See Also

`glmnet`, `predict` and `coef` methods.

### Examples

    x = matrix(rnorm(100 * 20), 100, 20)
    y = rnorm(100)
    fit1 = cv.glmnet(x, y)
    print(fit1)
    fit1r = cv.glmnet(x, y, relax = TRUE)
    print(fit1r)
    ## print.cv.glmnet(fit1r)  ## CHECK WITH TREVOR

[Package glmnet version 4.1 Index]