print.glintnet: Print a summary of the glintnet path at each step along the...

In adelie: Group Lasso and Elastic Net Solver for Generalized Linear Models

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 \Sexpr[results=rd]{tools:::Rd_expr_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)

adelie documentation built on April 3, 2025, 8:58 p.m.