print.glintnet {adelie} | R Documentation |
Print a summary of the glintnet path at each step along the path.
Description
Print a summary of the grpnet path at each step along the path.
Usage
## S3 method for class 'glintnet'
print(x, digits = max(3, getOption("digits") - 3), ...)
Arguments
x |
fitted glintnet object |
digits |
significant digits in printout |
... |
additional print arguments |
Details
The call that produced the object x
is printed, followed by a
five-column matrix with columns N_main
, N_int
, Df
, %Dev
and Lambda
.
The N_main
column is the number of main-effect terms in the solution, and N_int
the number of interaction terms. Since an interaction term implies both main effects, the former is always at least as large as the latter.
The Df
column is the number of nonzero coefficients (Df is a
reasonable name only for lasso fits). %Dev
is the percent deviance
explained (relative to the null deviance).
Value
The matrix above is silently returned
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
, plot
and coef
methods.
Examples
x = matrix(rnorm(100 * 20), 100, 20)
y = rnorm(100)
fit1 = grpnet(x, glm.gaussian(y), groups = c(1:5,7,9))
print(fit1)