dfCompile.glmnet: Create visualization matrix for a glmnet object
In benjaminleroy/ggDiagnose: Wrapper for Diagnostic Plots with ggplot2

Description Usage Arguments Details Value See Also Examples

For the graphic one could consider this just a smart "melting" ( reshape2's melt) of the beta matrix in the glmnet object.

1	dfCompile.glmnet(x)

`x`	`glmnet` object from `glmnet` library

data frame returned has the following columns:

.log.lambda: log(lambda) for the lambda values examined
variable: name of variable in the model
beta.value: for the specific variable when log(lambda) was .log.lambda
.norm: The L_1 norm of the beta values for specific each .log.lambda. That is, ∑_{i=1}^p beta_i(λ)
.dev: deviance ratio, the fraction of (null) deviance explained by the model. The deviance is defined to be 2*(loglike_sat - loglike), where loglike_sat is the log-likelihood for the saturated model (a model with a free parameter per observation). Hence .dev=1-dev/nulldev.
.number.non.zero: number of beta for that .log.lambda value that were non-zero

data frame, see details.

broom's tidy and use with the same object.

library(tidyverse)
library(glmnet)
glmnet.object <- glmnet(y = iris$Sepal.Length,
                        x = model.matrix(Sepal.Length~., data = iris))

dfCompile.glmnet(glmnet.object) %>% head