pmml.nnet: Generate the PMML representation for a nnet object from...

In pmml: Generate PMML for Various Models

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

Description

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

Usage

## S3 method for class 'nnet'
pmml(
  model,
  model_name = "NeuralNet_model",
  app_name = "SoftwareAG PMML Generator",
  description = "Neural Network Model",
  copyright = NULL,
  model_version = NULL,
  transforms = NULL,
  missing_value_replacement = NULL,
  ...
)

Arguments

model	A nnet 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.
...	Further arguments passed to or from other methods.

Details

This function supports both regression and classification neural network models. The model is represented in the PMML NeuralNetwork format.

Value

PMML representation of the nnet object.

Author(s)

Tridivesh Jena

References

nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models (on CRAN)

Examples

## Not run: 
library(nnet)
fit <- nnet(Species ~ ., data = iris, size = 4)
fit_pmml <- pmml(fit)

rm(fit)

## End(Not run)

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