pmml.randomForest: Generate PMML for randomForest objects

Description

Generate the PMML representation for a randomForest object from package randomForest.

Usage

# S3 method for randomForest
pmml(model, model.name="randomForest_Model",
      app.name="Rattle/PMML", 
      description="Random Forest Tree Model",
      copyright=NULL, transforms=NULL, unknownValue=NULL,
      parentInvalidValueTreatment="returnInvalid",
      childInvalidValueTreatment="asIs", ...)

Arguments

model

a randomForest object.

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 element 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.

parentInvalidValueTreatment

invalid value treatment at the top MiningField level.

childInvalidValueTreatment

invalid value treatment at the model segment MiningField level.

…

further arguments passed to or from other methods.

Details

This function outputs a Random Forest in PMML format. The model will include not just the forest but also any pre-processing applied to the training data.

References

R project CRAN package: randomForest: Breiman and Cutler's random forests for classification and regression https://CRAN.R-project.org/package=randomForest

Examples

Run this code

# NOT RUN {
# Build a simple randomForest model

library(randomForest)
iris.rf <- randomForest(Species ~ ., data=iris, ntree=20)

# Convert to pmml

pmml(iris.rf)

rm(iris.rf)

# }