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

## S3 method for class 'gg_minimal_depth':
plot(x, selection = FALSE, type = c("named",
  "rank"), lbls, ...)

Arguments

gg_minimal_depth object created from a randomForestSRC::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.

Examples

Run this code

#' ## Examples from RFSRC package...
## ------------------------------------------------------------
## classification example
## ------------------------------------------------------------
## You can build a randomForest
# iris_rf <- rfsrc(Species ~ ., data = iris)
# iris_vs <- var.select(iris_rf)
# ... or load a cached randomForestSRC object
data(iris_vs, package="ggRandomForests")

# Get a data.frame containing minimaldepth measures
gg_dta<- gg_minimal_depth(iris_vs)

# Plot the gg_mkinimal_depth object
plot(gg_dta)

## ------------------------------------------------------------
## Regression example
## ------------------------------------------------------------
# airq_rf <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")
# airq_vs <- var.select(airq_rf)
# ... or load a cached randomForestSRC object
data(airq_vs, package="ggRandomForests")

# Get a data.frame containing error rates
gg_dta<- gg_minimal_depth(airq_vs)

# Plot the gg_error object
plot(gg_dta)

## ------------------------------------------------------------
## Survival example
## ------------------------------------------------------------
## veteran data
## randomized trial of two treatment regimens for lung cancer
# data(veteran, package = "randomForestSRC")
# veteran_rf <- rfsrc(Surv(time, status) ~ ., data = veteran, ntree = 100)
# veteran_vs <- var.select(veteran_rf)
# Load a cached randomForestSRC object
data(veteran_vs, package="ggRandomForests")

gg_dta <- gg_minimal_depth(veteran_vs)
plot(gg_dta)