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

Description

A cached object from randomForestSRC::var.select function for the randomForestSRC regression forest mtcars_rf.

Arguments

format

A var.select object for a regression 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 (mtcars_rf) with the mtcars Motor Trend Car Road Tests data, then run the randomForestSRC::var.select function to determine minimal depth variable selection.

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

The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models).

References

Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391-411.

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.

Examples

Run this code

## The data was built with the following command
mtcars_rf <- rfsrc(mpg ~ ., data = mtcars)
airq_vs <- var.select(mtcars_rf)

gg_dta <- gg_minimal_depth(mtcars_vs)
plot(gg_dta)

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