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

Generate the multinomial logistic model in the PMML RegressionModel format. The function implements the use of numerical, categorical and multiplicative terms involving both numerical and categorical variables.

# S3 method for multinom
pmml(
  model,
  model_name = "multinom_Model",
  app_name = "SoftwareAG PMML Generator",
  description = "Multinomial Logistic Model",
  copyright = NULL,
  model_version = NULL,
  transforms = NULL,
  missing_value_replacement = NULL,
  ...
)

Arguments

model

A multinom 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.

Value

PMML representation of the multinom object.

References

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

Author

Tridivesh Jena

Examples

if (FALSE) {
library(nnet)
fit <- multinom(Species ~ ., data = iris)
fit_pmml <- pmml(fit)
}