Plotting variable importance measures
This function produces lattice and ggplot plots of objects with class "varImp.train". More info will be forthcoming.
## S3 method for class 'varImp.train' plot(x, top = dim(x$importance)[1], ...) ## S3 method for class 'varImp.train' ggplot( data, mapping = NULL, top = dim(data$importance)[1], ..., environment = NULL )
x, data |
an object with class |
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
( |
mapping, environment |
unused arguments to make consistent with ggplot2 generic method |
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.
a lattice plot object
Max Kuhn
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