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).
| Version: |
1.5.0 |
| Depends: |
XML |
| Imports: |
survival, methods, stats, utils |
| Suggests: |
ada, amap, arules, glmnet, nnet, rpart, randomForestSRC, randomForest, kernlab, e1071, pmmlTransformations (≥
1.3.0), testthat |
| Published: |
2015-08-05 |
| Author: |
Graham Williams, Tridivesh Jena, Wen Ching Lin, Michael Hahsler (arules),
Zementis Inc, Hemant Ishwaran, Udaya B. Kogalur, Rajarshi Guha, Dmitriy Bolotov |
| Maintainer: |
Tridivesh Jena <rpmmlsupport at zementis.net> |
| License: |
GPL (≥ 2.1) |
| URL: |
http://zementis.com/ |
| NeedsCompilation: |
no |
| Materials: |
ChangeLog |
| CRAN checks: |
pmml results |