The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define statistical and data mining models and to share models between PMML compliant applications. More information about PMML and the Data Mining Group can be found at http:// www.dmg.org. The generated PMML can be imported into any PMML consuming application, such as the Zementis ADAPA and UPPI scoring engines which allow for predictive models built in R to be deployed and executed on site, in the cloud (Amazon, IBM, and FICO), in-database (IBM Netezza, Pivotal, Sybase IQ, Teradata and Teradata Aster) or Hadoop (Datameer and Hive).

Documentation

Manual: pmml.pdf
Vignette: None available.

Maintainer: Tridivesh Jena <rpmmlsupport at zementis.net>

Author(s): Graham Williams, Tridivesh Jena, Wen Ching Lin, Michael Hahsler (arules), Zementis Inc, Hemant Ishwaran, Udaya B. Kogalur, Rajarshi Guha, Dmitriy Bolotov

Install package and any missing dependencies by running this line in your R console:

install.packages("pmml")

Depends XML
Imports methods, stats, utils, stringr
Suggests ada, amap, arules, gbm, glmnet, neighbr, nnet, rpart, randomForestSRC, randomForest, kernlab, e1071, testthat, survival, xgboost, pmmlTransformations(>=1.3.1)
Enhances
Linking to
Reverse
depends
Reverse
imports
RKEEL
Reverse
suggests
arules, partykit, pmmlTransformations, rattle
Reverse
enhances
Reverse
linking to

Package pmml
Materials
URL http://zementis.com/
Task Views
Version 1.5.2
Published 2017-02-27
License GPL (>= 2.1)
BugReports
SystemRequirements
NeedsCompilation no
Citation
CRAN checks pmml check results
Package source pmml_1.5.2.tar.gz