pmml.rfsrc {pmml} | R Documentation |
Generate the PMML representation for a randomSurvivalForest forest object.
## S3 method for class 'rfsrc' pmml(model, model.name="rsf_Model", app.name="Rattle/PMML", description="Random Survival Forest Model", copyright=NULL, transforms=NULL, unknownValue=NULL, ...)
model |
a |
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. |
copyright |
the copyright notice for the model. |
transforms |
data transformations represented in PMML via package pmmlTransformations. |
unknownValue |
value to be used as the 'missingValueReplacement' attribute for all MiningFields. |
... |
further arguments passed to or from other methods. |
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
.
Zementis Inc. info@zementis.com
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.
library(randomForestSRC) data(veteran) veteran.out <- rfsrc(Surv(time, status)~., data = veteran, ntree = 5, forest = TRUE) pmml(veteran.out)