Learn R Programming

ggRandomForests (version 2.0.1)

plot.gg_minimal_vimp: Plot a gg_minimal_vimp object for comparing the Minimal Depth and VIMP variable rankings.

Description

Plot a gg_minimal_vimp object for comparing the Minimal Depth and VIMP variable rankings.

Usage

"plot"(x, nvar, lbls, ...)

Arguments

x
gg_minimal_depth object created from a var.select object
nvar
should the figure be restricted to a subset of the points.
lbls
a vector of alternative variable names.
...
optional arguments (not used)

Value

ggplot object

See Also

gg_minimal_vimp var.select

Examples

Run this code
## 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_vimp(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)
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_vimp(varsel_airq)
# 
# # Plot the gg_minimal_vimp object
# plot(gg_dta)
# 
# ## -------- Boston data
# data(varsel_Boston, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_vimp(varsel_Boston)
# 
# # Plot the gg_minimal_vimp object
# plot(gg_dta)
# 
# ## -------- mtcars data
# data(varsel_mtcars, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_vimp(varsel_mtcars)
# 
# # Plot the gg_minimal_vimp object
# plot(gg_dta)
# 
# ## ------------------------------------------------------------
# ## Survival example
# ## ------------------------------------------------------------
# ## -------- 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_vimp(varsel_veteran)
# plot(gg_dta)
#   
# ## -------- pbc data
# data(varsel_pbc, package="ggRandomForests")
# 
# gg_dta <- gg_minimal_vimp(varsel_pbc)
# plot(gg_dta)
# ## End(Not run) 

Run the code above in your browser using DataLab