# plot.varImp.train

##### Plotting variable importance measures

This function produces lattice and ggplot plots of objects with class "varImp.train". More info will be forthcoming.

- Keywords
- hplot

##### Usage

```
# S3 method for varImp.train
plot(x, top = dim(x$importance)[1], ...)
```# S3 method for varImp.train
ggplot(
data,
mapping = NULL,
top = dim(data$importance)[1],
...,
environment = NULL
)

##### Arguments

- x, data
an object with class

`varImp`

.- top
a scalar numeric that specifies the number of variables to be displayed (in order of importance)

- …
arguments to pass to the lattice plot function (

`dotplot`

and`panel.needle`

)- mapping, environment
unused arguments to make consistent with ggplot2 generic method

##### Details

For models where there is only one importance value, such a regression
models, a "Pareto-type" plot is produced where the variables are ranked by
their importance and a needle-plot is used to show the top variables.
Horizontal bar charts are used for `ggplot`

.

When there is more than one importance value per predictor, the same plot is produced within conditioning panels for each class. The top predictors are sorted by their average importance.

##### Value

a lattice plot object

*Documentation reproduced from package caret, version 6.0-85, License: GPL (>= 2)*