The Predictive Modelling Markup Language (PMML) is a language
for representing models, in an application independent way. Such models
can then be loaded into other applications supporting PMML, including
ADAPA from Zementis, Teradata Warehouse Miner and IBM's DB2.
The package provides a generic pmml function to generate pmml for an
object. Using a S3 generic function the approriate method for the
class of the supplied object is dispatched.
The package currently supports the export of PMML for linear
regression, SVMs, rpart classification trees,
randomSurvivalForest forest models, and kmeans clusters.
This package is part of the Rattle toolkit.

Graham Williams,  Zementis Inc, Hemant Ishwaran, Udaya B. Kogalur,
Rajarshi Guha
nnet, rpart, randomSurvivalForest, randomForest, kernlab

Graham Williams, Michael Hahsler (arules), Zementis Inc,
Hemant Ishwaran, Udaya B. Kogalur, Rajarshi Guha
arules, nnet, rpart, randomSurvivalForest, randomForest, kernlab

Graham Williams, Michael Hahsler (arules), Zementis Inc, Hemant
Ishwaran, Udaya B. Kogalur, Rajarshi Guha
arules, nnet, rpart, randomSurvivalForest, randomForest,
kernlab
The Predictive Modelling Markup Language (PMML) is a
language for representing models, in an application independent
way. Such models can then be loaded into other applications
supporting PMML, including ADAPA from Zementis, Teradata
Warehouse Miner and IBM's DB2. The package provides a generic
pmml function to generate pmml for an object. Using a S3
generic function the approriate method for the class of the
supplied object is dispatched. The package currently supports
the export of PMML for linear regression, SVMs, rpart
classification trees, randomSurvivalForest forest models, and
kmeans clusters. This package is part of the Rattle toolkit.

The Predictive Modelling Markup Language (PMML) is a
language for representing models using XML in an application
independent way. Such models can then be shared with other
applications that support PMML (see
http://www.dmg.org/products.html). The generic pmml() function
takes an R model as its argument and returns the corresponding
PMML.  Currently supported models for export include linear
regression (lm and glm), support vector machines (ksvm),
decision trees (rpart), neural networks (nnet, multinom),
association rules (arules), survival models (coxph, survreg),
random survival forests (randomSurvivalForest), and clusters
(kmeans, hclust).