Which statement accurately describes PMML models?

The accurate statement about PMML models is that PMML compliant models can indeed be used in the same strategies as Pega's own predictive models. PMML, or Predictive Model Markup Language, is an XML-based language that allows for the sharing of predictive models between different systems. This interoperability is key in the realm of decisioning and predictive analytics.

Using PMML models alongside Pega's predictive models allows organizations to leverage external modeling capabilities while still integrating smoothly with Pega's decision-making infrastructure. This means that businesses can utilize the predictive insights generated by models developed outside of Pega, maintaining flexibility and enhancing their decisioning strategies.

The other statements misrepresent the capabilities of PMML models. They imply either restrictions on their usage or erroneous processes related to converting models, which does not accurately reflect how Pega's systems are designed to handle PMML compliant models. The strength of PMML lies in its ability to facilitate model interchangeability and integration, which Pega embraces in its framework.