autoplot methods for ggRandomForests data objects

These let you call ggplot2::autoplot() on any gg_* object ggRandomForests returns. Each is a thin wrapper around the matching plot.gg_*() S3 method, and ... passes straight through, so every argument those plot methods take is still available here.

Usage

# S3 method for class 'gg_error'
autoplot(object, ...)

# S3 method for class 'gg_vimp'
autoplot(object, ...)

# S3 method for class 'gg_rfsrc'
autoplot(object, ...)

# S3 method for class 'gg_variable'
autoplot(object, ...)

# S3 method for class 'gg_partial'
autoplot(object, ...)

# S3 method for class 'gg_partial_rfsrc'
autoplot(object, ...)

# S3 method for class 'gg_partialpro'
autoplot(object, ...)

# S3 method for class 'gg_partial_varpro'
autoplot(object, ...)

# S3 method for class 'gg_roc'
autoplot(object, ...)

# S3 method for class 'gg_survival'
autoplot(object, ...)

# S3 method for class 'gg_brier'
autoplot(object, ...)

# S3 method for class 'gg_varpro'
autoplot(object, ...)

# S3 method for class 'gg_udependent'
autoplot(object, ...)

# S3 method for class 'gg_isopro'
autoplot(object, ...)

Arguments

object

A gg_* data object (see Details).

...

Additional arguments passed to the underlying plot.gg_*() method.

Value

A ggplot object.

Details

The following gg_* classes are supported:

gg_error

OOB error vs. number of trees

gg_vimp

Variable importance ranking

gg_rfsrc

Predicted vs. observed values

gg_variable

Marginal dependence

gg_partial

Partial dependence (via plot.variable)

gg_partial_rfsrc

Partial dependence (via partial.rfsrc)

gg_partial_varpro

Partial dependence (via varPro)

gg_partialpro

Partial dependence via varPro (deprecated alias)

gg_varpro

Variable importance from varPro

gg_roc

ROC curve

gg_survival

Survival / cumulative hazard curves

gg_brier

Time-resolved Brier score and CRPS

Examples

# \donttest{
library(ggplot2)
set.seed(42)
rf <- randomForestSRC::rfsrc(Ozone ~ ., data = na.omit(airquality),
                              ntree = 50, importance = TRUE,
                              tree.err = TRUE)
autoplot(gg_error(rf))

autoplot(gg_vimp(rf))

# }