pmml | R Documentation |
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, copyright = NULL, model_version = NULL, transforms = NULL, ... )
model |
An object to be converted to PMML. |
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. |
... |
Further arguments passed to or from other methods. |
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 4.4.1.
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")
.
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
.
Graham Williams
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.rpart
, pmml.svm
,
pmml.xgb.Booster
# 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)
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