Generate the PMML representation for a nnet object from package nnet.
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, 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. |
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
library(nnet) fit <- nnet(Species ~ ., data = iris, size = 4) fit_pmml <- pmml(fit) rm(fit)
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