R is becoming the tool of choice for many data scientists. It is no wonder that many commercial and open-source statistical tools are also embracing R.
Predictive Models
A set of robust predictive analytic techniques is but one set of tools available to data scientists in R. Another important set is the ability to export PMML for a host of predictive models.
By using the pmml package (version 1.2.33 or higher), users can export PMML from R for:
Random Forest Models
Neural Networks
Clustering Models
Cox Regression Models
Linear and Logistic Regression Models
Support Vector Machines
Association Rules
Generalized Linear Models
Random Survival Forest Models
Data Transformations
And now, another R package extends this functionality by providing PMML export for data transformations. The new pmmlTransformations package has just made its way to CRAN (the Comprehensive R Archive Network).
Want to apply a Z-scoring normalization procedure to your continuous input variables before presenting them to a neural network? No problem. Use the pmmlTransformations package in conjunction with the pmml package (version 1.2.33 or higher) to export the entire process (pre-processing + model) into a PMML file.
To look at the package’s documentation in CRAN, click HERE.
Agile Predictive Analytics Deployment
Once represented as a PMML file, a predictive solution (data transformations + model) can be readily moved into the operational environment where it can be put to work immediately. That’s the promise of PMML.
Zementis offers a host of products for the agile deployment and execution of your PMML-based solutions. Our ADAPA and UPPI scoring engines are available for:
Hadoop: Datameer and Hadoop/Hive
In-database: EMC Greenplum, IBM Netezza, SAP Sybase IQ, Teradata, and Teradata Aster
Cloud: Amazon EC2 and IBM SmartCloud Enterprise
On-site: On your own servers
Real-time or Big Data requirements? Zementis has you covered.
Contact us today for more information or to schedule a presentation/demo.
Open source tools provide a cost-effective, yet powerful option for data mining. The following contenders adhere to the PMML standard which facilitates model exchange among open source and commercial vendors, providing a definitive route for production deployment of predictive models. The R ProjectThe R Project for Statistical Computing is definitely…
The ADAPA Decision Engine provides additional value to all your predictive assets. It is complimentary to R, since it extends your modeling environment into the IT operational domain. ADAPA® is compatible with R through PMML, the Predictive Model Markup Language, which is the de facto standard to represent predictive models.…
If you'd like to learn more about using the PMML package in R to export statistical models, or if you'd just like to learn more about building predictive models in Revolution R and creating predictions (scores) from them in other applications or in the cloud, I'll be co-presenter on a…