pmml.rpart: Generate the PMML representation for an rpart object from the...

In pmml: Generate PMML for Various Models

Generate the PMML representation for an rpart object from the package rpart.

Description

Generate the PMML representation for an rpart object from the package rpart.

Usage

## S3 method for class 'rpart'
pmml(
  model,
  model_name = "RPart_Model",
  app_name = "SoftwareAG PMML Generator",
  description = "RPart Decision Tree Model",
  copyright = NULL,
  model_version = NULL,
  transforms = NULL,
  missing_value_replacement = NULL,
  dataset = NULL,
  ...
)

Arguments

model	An rpart object.
model_name	A name to be given to the PMML model.
app_name	The name of the application that generated the PMML.
description	A descriptive text for the Header element of the PMML.
copyright	The copyright notice for the model.
model_version	A string specifying the model version.
transforms	Data transformations.
missing_value_replacement	Value to be used as the 'missingValueReplacement' attribute for all MiningFields.
dataset	Data used to train the rpart model.
...	Further arguments passed to or from other methods.

Details

Supports regression tree as well as classification. The object is represented in the PMML TreeModel format.

Value

PMML representation of the rpart object.

Author(s)

Graham Williams

References

rpart: Recursive Partitioning (on CRAN)

Examples

## Not run: 
library(rpart)

fit <- rpart(Species ~ ., data = iris)

fit_pmml <- pmml(fit)

## End(Not run)

pmml documentation built on March 18, 2022, 5:49 p.m.