pmml is a generic function implementing S3 methods used to produce the PMML (Predictive Model Markup Language) representation of an R model. The resulting PMML file can then be imported into other systems that accept PMML.

pmml(
model = NULL,
model_name = "R_Model",
app_name = "SoftwareAG PMML Generator",
description = NULL,
transforms = NULL,
...
)

## Arguments

model An object to be converted to PMML. A name to be given to the PMML model. The name of the application that generated the PMML. A descriptive text for the Header element of the PMML. The copyright notice for the model. Data transformations. Further arguments passed to or from other methods.

## Value

An object of class XMLNode as that defined by the XML package. This represents the top level, or root node, of the XML document and is of type PMML. It can be written to file with saveXML.

## Details

The data transformation functions previously available in the separate pmmlTransformations package have been merged into pmml starting with version 2.0.0.

This function can also be used to output variable transformations in PMML format. In particular, it can be used as a transformations generator. Various transformation operations can be implemented in R and those transformations can then be output in PMML format by calling the function with a NULL value for the model input and a data transformation object as the transforms input. Please see the documentation for xform_wrap for more information on how to create a data transformation object.

In addition, the pmml function can also be called using a pre-existing PMML model as the first input and a data transformation object as the transforms input. The result is a new PMML model with the transformation inserted as a "LocalTransformations" element in the original model. If the original model already had a "LocalTransformations" element, the new information will be appended to that element. If the model variables are derived directly from a chain of transformations defined in the transforms input, the field names in the model are replaced with the original field names with the correct data types to make a consistent model. The covered cases include model fields derived from an original field, model fields derived from a chain of transformations starting from an original field and multiple fields derived from the same original field.

This package exports models to PMML version 4.4.

Please note that package XML_3.95-0.1 or later is required to perform the full and correct functionality of pmml.

If data used for an R model contains features of type character, these must be converted to factors before the model is trained and converted with pmml.

A list of all the supported models and packages is available in the vignette:

vignette("packages_and_functions", package="pmml").

## References

pmml.ada, pmml.rules, pmml.coxph, pmml.cv.glmnet, pmml.glm, pmml.hclust, pmml.kmeans, pmml.ksvm, pmml.lm, pmml.multinom, pmml.naiveBayes, pmml.neighbr, pmml.nnet, pmml.randomForest, pmml.rfsrc, pmml.rpart, pmml.svm, pmml.xgb.Booster

## Examples

# Build an lm model
iris_lm <- lm(Sepal.Length ~ ., data = iris)

# Convert to pmml
iris_lm_pmml <- pmml(iris_lm)

# Create a data transformation object
iris_trans <- xform_wrap(iris)

# Transform the 'Sepal.Length' variable
iris_trans <- xform_min_max(iris_trans, xform_info = "column1->d_sl")

# Output the tranformation in PMML format
iris_trans_pmml <- pmml(NULL, transforms = iris_trans)