plot.gg_interaction: plot.gg_interaction Plot a 'gg_interaction' object,

In ggRandomForests: Visually Exploring Random Forests

plot.gg_interaction Plot a gg_interaction object,

Description

plot.gg_interaction Plot a gg_interaction object,

Usage

## S3 method for class 'gg_interaction'
plot(x, xvar, lbls, ...)

Arguments

x	gg_interaction object created from a rfsrc object
xvar	variable (or list of variables) of interest.
lbls	A vector of alternative variable names.
...	arguments passed to the gg_interaction function.

Value

ggplot object

References

Breiman L. (2001). Random forests, Machine Learning, 45:5-32.

Ishwaran H. and Kogalur U.B. (2007). Random survival forests for R, Rnews, 7(2):25-31.

Ishwaran H. and Kogalur U.B. (2013). Random Forests for Survival, Regression and Classification (RF-SRC), R package version 1.4.

See Also

rfsrc find.interaction max.subtree var.select vimp plot.gg_interaction

Examples

## Not run: 
## Examples from randomForestSRC package...
## ------------------------------------------------------------
## find interactions, classification setting
## ------------------------------------------------------------
## -------- iris data
## iris.obj <- rfsrc(Species ~., data = iris)
## TODO: VIMP interactions not handled yet....
## find.interaction(iris.obj, method = "vimp", nrep = 3)
## interaction_iris <- find.interaction(iris.obj)
data(interaction_iris, package="ggRandomForests")
gg_dta <- gg_interaction(interaction_iris)

plot(gg_dta, xvar="Petal.Width")
plot(gg_dta, xvar="Petal.Length")
plot(gg_dta, panel=TRUE)

## ------------------------------------------------------------
## find interactions, regression setting
## ------------------------------------------------------------
## -------- air quality data
## airq.obj <- rfsrc(Ozone ~ ., data = airquality)
##
## TODO: VIMP interactions not handled yet....
## find.interaction(airq.obj, method = "vimp", nrep = 3)
## interaction_airq <- find.interaction(airq.obj)
data(interaction_airq, package="ggRandomForests")
gg_dta <- gg_interaction(interaction_airq)

plot(gg_dta, xvar="Temp")
plot(gg_dta, xvar="Solar.R")
plot(gg_dta, panel=TRUE)

## -------- Boston data
data(interaction_boston, package="ggRandomForests")
gg_dta <- gg_interaction(interaction_boston)

plot(gg_dta, panel=TRUE)

## -------- mtcars data
data(interaction_mtcars, package="ggRandomForests")
gg_dta <- gg_interaction(interaction_mtcars)

plot(gg_dta, panel=TRUE)

## ------------------------------------------------------------
## find interactions, survival setting
## ------------------------------------------------------------
## -------- pbc data
## data(pbc, package = "randomForestSRC")
## pbc.obj <- rfsrc(Surv(days,status) ~ ., pbc, nsplit = 10)
## interaction_pbc <- find.interaction(pbc.obj, nvar = 8)
data(interaction_pbc, package="ggRandomForests")
gg_dta <- gg_interaction(interaction_pbc)

plot(gg_dta, xvar="bili")
plot(gg_dta, xvar="copper")
plot(gg_dta, panel=TRUE)

## -------- veteran data
data(interaction_veteran, package="ggRandomForests")
gg_dta <- gg_interaction(interaction_veteran)

plot(gg_dta, panel=TRUE)


## End(Not run)

ggRandomForests documentation built on Sept. 1, 2022, 5:07 p.m.