The Predictive Model Markup Language aka `PMML` is an `XML`-based markup language developed by the Data Mining Group (DMG) to provide a way for applications to define models related to predictive analytics and data mining and to share those models between `PMML`-compliant applications.
The Predictive Model Markup Language aka PMML is an XML-based markup language developed by the Data Mining Group (DMG) to provide a way for applications to define models related to predictive analytics and data mining and to share those models between PMML-compliant applications.
PMML provides applications a vendor-independent method of defining models so that proprietary issues and incompatibilities are no longer a barrier to the exchange of models between applications. It allows users to develop models within one vendor's application and use other vendors' applications to visualize, analyze, evaluate or otherwise use the models. Previously, this was very difficult, but with PMML, the exchange of models between compliant applications is straightforward.
Since PMML is an XML-based standard, the specification comes in the form of an XML schema.
Although PMML is the first and still most widely-used standard for machine learning and regression models, the DMG more recently created a JSON-based standard, Portable Format for Analytics (PFA) which includes more flexibility for pre- and post-processing by abstracting general math operations as PFA documents.
References:
PMML: An Open Standard for Sharing Models in The R Journal, Vol. 1/1, May 2009
PMML standard v4.3 at dmg.org
