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ggRandomForests (version 1.1.1)

veteran_vs: Minimal depth variable selection object (randomForestSRC::var.select).

Description

A cached object from randomForestSRC::var.select function for the Veteran's Administration Lung Cancer Trial survival forest veteran_rf.

Arguments

format

A var.select object for the veteran survival random forest

Details

For ggRandomForest testing and the R CMD checks, we cache the computationally expensive parts of running a randomForest.

We build a regression randomForest (veteran_rf) with the veteran clinical trial data, then run the randomForestSRC::var.select function to determine minimal depth variable selection.

This "data set" is a cache of the randomForestSRC::var.select function, which runs the minimal depth variable selection method from the veteran_rf random forest model.

The Veteran's Administration Lung Cancer Trial is a randomized trial of two treatment regimens for lung cancer. This is a standard survival analysis data set.

  • trt treatment: 1=standard 2=test
  • celltype cell-type: 1=squamous, 2=smallcell, 3=adeno, 4=large
  • time survival time
  • status censoring status
  • karno Karnofsky performance score (100=good)
  • diagtime months from diagnosis to randomisation
  • age age in years
  • prior prior therapy 0=no, 1=yes

References

Kalbfleisch J. and Prentice R, (1980) The Statistical Analysis of Failure Time Data. New York: Wiley.

Ishwaran H. and Kogalur U.B. (2014). Random Forests for Survival, Regression and Classification (RF-SRC), R package version 1.5.4.

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

Ishwaran H., Kogalur U.B., Blackstone E.H. and Lauer M.S. (2008). Random survival forests. Ann. Appl. Statist. 2(3), 841-860.

See Also

veteran randomForestSRC::var.select randomForestSRC::rfsrc veteran_rf gg_minimal_depth plot.gg_minimal_depth

var.select rfsrc veteran

Examples

Run this code
## The data was built with the following commands
## 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)

gg_dta <- gg_minimal_depth(veteran_vs)
plot(gg_dta)

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