ggRandomForests (version 2.0.1)

plot.gg_minimal_depth: Plot a gg_minimal_depth object for random forest variable ranking.

Description

Plot a gg_minimal_depth object for random forest variable ranking.

Usage

"plot"(x, selection = FALSE, type = c("named", "rank"), lbls, ...)

Arguments

x

gg_minimal_depth object created from a rfsrc object

selection

should we restrict the plot to only include variables selected by the minimal depth criteria (boolean).

type

select type of y axis labels c("named","rank")

lbls

a vector of alternative variable names.

...

optional arguments passed to gg_minimal_depth

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. (2014). Random Forests for Survival, Regression and Classification (RF-SRC), R package version 1.5.

See Also

var.select gg_minimal_depth

Examples

## Not run: 
# ## Examples from RFSRC package... 
# ## ------------------------------------------------------------
# ## classification example
# ## ------------------------------------------------------------
# ## -------- iris data
# ## You can build a randomForest
# # rfsrc_iris <- rfsrc(Species ~ ., data = iris)
# # varsel_iris <- var.select(rfsrc_iris)
# # ... or load a cached randomForestSRC object
# data(varsel_iris, package="ggRandomForests")
# 
# # Get a data.frame containing minimaldepth measures
# gg_dta<- gg_minimal_depth(varsel_iris)
# 
# # Plot the gg_minimal_depth object
# plot(gg_dta)
# 
# ## ------------------------------------------------------------
# ## Regression example
# ## ------------------------------------------------------------
# ## -------- air quality data
# # rfsrc_airq <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")
# # varsel_airq <- var.select(rfsrc_airq)
# # ... or load a cached randomForestSRC object
# data(varsel_airq, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_depth(varsel_airq)
# 
# # Plot the gg_minimal_depth object
# plot(gg_dta)
# 
# ## -------- Boston data
# data(varsel_Boston, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# plot(gg_minimal_depth(varsel_Boston))
# 
# ## -------- mtcars data
# data(varsel_mtcars, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# plot.gg_minimal_depth(varsel_mtcars)
# 
# ## ------------------------------------------------------------
# ## Survival example
# ## ------------------------------------------------------------
# ## -------- veteran data
# ## veteran data
# ## randomized trial of two treatment regimens for lung cancer
# # data(veteran, package = "randomForestSRC")
# # rfsrc_veteran <- rfsrc(Surv(time, status) ~ ., data = veteran, ntree = 100)
# # varsel_veteran <- var.select(rfsrc_veteran)
# # Load a cached randomForestSRC object
# data(varsel_veteran, package="ggRandomForests")
# 
# gg_dta <- gg_minimal_depth(varsel_veteran)
# plot(gg_dta)
# 
# ## -------- pbc data
# data(varsel_pbc, package="ggRandomForests")
# 
# gg_dta <- gg_minimal_depth(varsel_pbc)
# plot(gg_dta)
# 
# ## End(Not run)