ggRandomForests (version 1.1.1)

airq_rf: Air quality randomForestSRC object.

Description

A cached randomForestSRC::rfsrc object for the New York Air Quality Measurements. This is a randomForestSRC regression forest.

format

A randomForestSRC::rfsrc object for regression

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.

We build a regression randomForest (airq_rf) with the airquality measurements data. 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.

See Also

airquality rfsrc airq_vs airq_interaction airq_prtl gg_rfsrc plot.gg_rfsrc gg_error plot.gg_error

Examples

## The data was built with the following command
airq_rf <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")

# Plot predicted values for the training data
gg_dta <- gg_rfsrc(airq_rf)
plot(gg_dta)

# Plot error rate for the forest
gg_dta <- gg_error(airq_rf)
plot(gg_dta)