ggRandomForests (version 1.2.1)

gg_interaction: Minimal Depth Variable Interaction data object (find.interaction).

Description

Converts the matrix returned from find.interaction to a data.frame and add attributes for S3 identification. If passed a rfsrc object, gg_interaction first runs the find.interaction function with all optional arguments.

Usage

gg_interaction(object, ...)

Arguments

object

a rfsrc object or the output from the find.interaction function call.

...

optional extra arguments passed to find.interaction.

Value

• gg_interaction object

References

Ishwaran H. (2007). Variable importance in binary regression trees and forests, Electronic J. Statist., 1:519-537.

Ishwaran H., Kogalur U.B., Gorodeski E.Z, Minn A.J. and Lauer M.S. (2010). High-dimensional variable selection for survival data. J. Amer. Statist. Assoc., 105:205-217.

Ishwaran H., Kogalur U.B., Chen X. and Minn A.J. (2011). Random survival forests for high-dimensional data. Statist. Anal. Data Mining, 4:115-132.

See Also

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

Examples

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

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

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

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

plot(gg_dta, panel=TRUE)