pmml.rfsrc: Generate PMML for rfsrc objects

Description

Generate the PMML representation for a randomSurvivalForest forest object.

Usage

# S3 method for rfsrc
pmml(model, model.name="rsf_Model",
      app.name="Rattle/PMML",
      description="Random Survival Forest Model",
      copyright=NULL, transforms=NULL, unknownValue=NULL, ...)

Arguments

model

a forest object contained in an object of class randomSurvivalForest, as that contained in the object returned by the function rfsrc with the parameter “forest=TRUE”.

model.name

a name to be given to the model in the PMML code.

app.name

the name of the application that generated the PMML code.

description

a descriptive text for the Header of the PMML code.

the copyright notice for the model.

transforms

data transformations represented in PMML via pmmlTransformations.

unknownValue

value to be used as the 'missingValueReplacement' attribute for all MiningFields.

…

further arguments passed to or from other methods.

Details

This function is used to export the geometry of the forest to other PMML compliant applications, including graphics packages that are capable of printing binary trees. In addition, the user may wish to save the geometry of the forest for later retrieval and prediction on new data sets using pmml.rfsrc together with pmml_to_rsf.

The pmml package supports randomSurvivalForest up to version 2.5.0.

References

H. Ishwaran, U.B. Kogalur, E.H. Blackstone, M.S. Lauer (2008), /emphRANDOM SURVIVAL FORESTS. The Annals of Applied Statistics, Vol. 2, No. 3, 841-860
H. Ishwaran and Udaya B. Kogalur (2006). Random Survival Forests. Cleveland Clinic Technical Report.

Examples

Run this code

# NOT RUN {
 # Works with randomForestSRC version 2.5.0.
 # library(randomForestSRC)
 # data(veteran)
 # veteran.out <- rfsrc(Surv(time, status)~., data = veteran, ntree = 5,
                      forest = TRUE, membership = TRUE)
 # pmml(veteran.out)
# }