airq_interaction: minimal depth interaction matrix from randomForestSRC::find.interaction.

Description

A cached object constructed from the randomForestSRC::find.interaction function for the New York Air Quality Measurements. The randomForestSRC regression forest is stored in the airq_rf object.

Arguments

format

rdata matrix from randomForestSRC::find.interaction

Details

For ggRandomForests examples and tests, as well as streamlining the R CMD CHECK for package release, we cache the computationally expensive operations from the randomForestSRC package.

To test the interaction plots, we build a regression randomForest (airq_rf) with the airquality measurements data, then run the find.interaction function to determine pairwise variable interaction measures.

The airq_interation "data set" is a cache of the find.interaction function, which measures pairwise interactions between variables from the airq_rf random forest model.

The data were from New York, from May to September 1973. The data was obtained from the New York State Department of Conservation (ozone data) and the National Weather Service (meteorological data).

References

Chambers, J. M., Cleveland, W. S., Kleiner, B. and Tukey, P. A. (1983) Graphical Methods for Data Analysis. Belmont, CA: Wadsworth.

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
airq_rf <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")
airq_interaction <- find.interaction(airq_rf)

gg_dta <- gg_interaction(airq_interaction)

plot(gg_dta, x_var="Temp")
plot(gg_dta, x_var="Solar.R")