Also see predictive modeling.
PMML (Predictive Model Markup Language) is an XML-based language that enables the definition and sharing of predictive models between applications. A predictive model is a statistical model that is designed to predict the likelihood of target occurrences given established variables or factors. Increasingly, predictive models are being used in e-business applications, such as customer relationship management (CRM) systems, to forecast business-related phenomena, such as customer behavior. The PMML specifications establish a vendor-independent means of defining these models, so that problems with proprietary applications and compatibility issues can be circumvented.
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The Data Mining Group (DMG), an independent vendor group whose membership includes IBM and Oracle, developed PMML as a means of simplifying processes involved in data mining. Because predictive models are created with statistical software, and then generally deployed by people using COBOL, C, or C++, working with and updating the models can be problematic. A PMML document contains definitions of analytic models and all the necessary information for deployment, so that a model can be worked with across various platforms, applications, and operating systems, independently of the software used to create them.