plot.glmnet

0th

Percentile

plot coefficients from a "glmnet" object

Produces a coefficient profile plot of the coefficient paths for a fitted "glmnet" object.

Keywords
models, regression
Usage
## S3 method for class 'glmnet':
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE, ...)
## S3 method for class 'multnet':
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE,type.coef=c("coef","2norm"), ...)
## S3 method for class 'mrelnet':
plot(x, xvar = c("norm", "lambda", "dev"), label = FALSE,type.coef=c("coef","2norm"), ...)
Arguments
x
fitted "glmnet" model
xvar
What is on the X-axis. "norm" plots against the L1-norm of the coefficients, "lambda" against the log-lambda sequence, and "dev" against the percent deviance explained.
label
If TRUE, label the curves with variable sequence numbers.
type.coef
If type.coef="2norm" then a single curve per variable, else if type.coef="coef", a coefficient plot per response
...
Other graphical parameters to plot
Details

A coefficient profile plot is produced. If x is a multinomial model, a coefficient plot is produced for each class.

References

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

See Also

glmnet, and print, predict and coef methods.

Aliases
  • plot.glmnet
  • plot.multnet
  • plot.mrelnet
Examples
x=matrix(rnorm(100*20),100,20)
y=rnorm(100)
g2=sample(1:2,100,replace=TRUE)
g4=sample(1:4,100,replace=TRUE)
fit1=glmnet(x,y)
plot(fit1)
plot(fit1,xvar="lambda",label=TRUE)
fit3=glmnet(x,g4,family="multinomial")
plot(fit3,pch=19)
Documentation reproduced from package glmnet, version 1.8-5, License: GPL-2

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