# print.glmnet

##### print a glmnet object

Print a summary of the glmnet path at each step along the path.

- Keywords
- models, regression

##### Usage

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

##### Arguments

- x
fitted glmnet object

- digits
significant digits in printout

- …
additional print arguments

##### Details

The call that produced the object `x`

is printed, followed by a
three-column matrix with columns `Df`

, `%Dev`

and `Lambda`

.
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). In the case of a 'relaxed' fit,
an additional column is inserted, `%Dev R`

which gives the percent
deviance explained by the relaxed model. For a "bigGlm" model, a simpler
summary is printed.

##### Value

The matrix above is silently returned

##### References

Friedman, J., Hastie, T. and Tibshirani, R. (2008). Regularization Paths for Generalized Linear Models via Coordinate Descent

##### See Also

`glmnet`

, `predict`

and `coef`

methods.

##### Examples

```
# NOT RUN {
x = matrix(rnorm(100 * 20), 100, 20)
y = rnorm(100)
fit1 = glmnet(x, y)
print(fit1)
# }
```

*Documentation reproduced from package glmnet, version 3.0-2, License: GPL-2*