pmml.nnet {pmml} | R Documentation |
Generate the PMML representation for a nnet object from package nnet.
## 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,
...
)
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. |
This function supports both regression and classification neural network models. The model is represented in the PMML NeuralNetwork format.
PMML representation of the nnet object.
Tridivesh Jena
nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models (on CRAN)
## Not run:
library(nnet)
fit <- nnet(Species ~ ., data = iris, size = 4)
fit_pmml <- pmml(fit)
rm(fit)
## End(Not run)