print.cv.glmnet

0th

Percentile

print a cross-validated glmnet object

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

Keywords
models, regression
Usage
# S3 method for 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.

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.

Aliases
  • print.cv.glmnet
  • print.cv.relaxed
Examples
# NOT RUN {
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
# }
Documentation reproduced from package glmnet, version 3.0-2, License: GPL-2

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