conformance standard for the predictive model markup language
One of the main objectives for the Predictive Model Markup Language (PMML) is to facilitate the exchange of models from one environment to another. For example, a model developed with one tool can be transferred via PMML to another tool for scoring. Or, a model can be documented in PMML and given to others for review, inspection or archival purposes. Exchanging predictive models between different products or environments requires a common understanding of the PMML specification. This understanding can be less than perfect, especially since PMML contains over 700 language elements, along with the ability to add product specific extensions. The result is that, even though there is a detailed PMML specification, models defined in PMML can vary in subtle ways from vendor to vendor. As pointed out in last year's KDD Workshop (DM-SSP 05), this lack of conformity reduces the usefulness of PMML and hampers the growth of its use by the data mining community [1]. A clear and compelling need for a conformance standard has been identified to improve the interoperability of PMML models, and to increase the reliability of PMML as a seamless, multi-vendor model exchange medium. This paper defines the state of the art in PMML and an approach under consideration for cross-vendor PMML conformance.
pmml data mining data mining predictive analysis business intelligence knowledge discovery database