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The Data Mining Group releases PMML v4.3


PMML is an application and system independent format for statistical and data mining models. Key PMML 4.3 features include Improved support for post-processing, model types, and model elements, and new models for Gaussian Process and Bayesian Networks. Check PMML session at KDD-16.



By Walt Wells, DMG.

PMML
The Data Mining Group (DMG) is pleased to announce the release of the Predictive Model Markup Language (PMML) v4.3.  PMML is an application and system independent XML interchange format for statistical and data mining models. The goal of the PMML standard is to encapsulate a model independent of applications or systems using an XML configuration file so that two different applications (the PMML Producer and Consumer) can use it.

As predictive analytics and data mining continue to gain momentum in industry and business applications across the internet of things, industrial internet, and instrumented environments, open standards like PMML provide a key platform to operationalize analytic models.   Though the surge of interest in predictive analytics is relatively new, the Data Mining Group and the PMML standard have been supporting the data science community nearly 20 years.  PMML v0.7 was first introduced in 1997.   DMG members active in the PMML working group that developed v4.3 include IBM, SAS, Zementis, Salford Systems, and NIST.

Some of the elements that are new to PMML v4.3 include:

  • Improved support for post-processing, model types, and model elements
  • New models for Gaussian Process and Bayesian Networks
  • New built-in functions for multiple probability distributions

A full list of updates can be found at: http://dmg.org/pmml/v4-3/Changes.html

The DMG has actively partnered with ACM SIGKDD (http://www.kdd.org/) to promote awareness of available standards for predictive analytics.  There will be a Special Session on “Standards in Predictive Analytics” on Tuesday, Aug 16 during the KDD 2016 conference in San Francisco, CA.  This special applied data science session will cover available standards, discuss their adoption, and explore any needs unmet by existing standards. This event forms part of a broader SIGKDD Standards Initiative and will be of particular interest to KDD attendees focused on the operational application of data mining.  For more information, visit:  http://dmg.org/kdd2016.html

About DMG:

The Data Mining Group (DMG) is an independent, vendor led consortium that develops data mining standards, such as the Predictive Model Markup Language (PMML) and Portable Format for Analytics (PFA).  
For more information about the Data Mining Group and the PMML standard, go to: www.dmg.org.

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