print.cv.grpnet {adelie} | R Documentation |
print a cross-validated grpnet object
Description
Print a summary of the results of cross-validation for a grpnet model.
Usage
## S3 method for class 'cv.grpnet'
print(x, digits = max(3, getOption("digits") - 3), ...)
Arguments
x |
fitted 'cv.grpnet' object |
digits |
significant digits in printout |
... |
additional print arguments |
Author(s)
James Yang, Trevor Hastie, and Balasubramanian Narasimhan
Maintainer: Trevor Hastie hastie@stanford.edu
References
Yang, James and Hastie, Trevor. (2024) A Fast and Scalable Pathwise-Solver for Group Lasso and Elastic Net Penalized Regression via Block-Coordinate Descent. arXiv doi:10.48550/arXiv.2405.08631.
See Also
grpnet
, predict
and coef
methods.
Examples
x = matrix(rnorm(100 * 20), 100, 20)
y = rnorm(100)
fit1 = cv.grpnet(x, glm.gaussian(y))
print(fit1)
[Package adelie version 1.0.8 Index]