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Deploying Advanced Analytics Using R & PMML
Allowing this data to remain unused and merely stored is wasteful. Data is increasingly being treated as a perishable asset, which is spurring business interest in predictive analytics.
The challenge for organizations has been a lack of technologies that can help programmers quickly and easily develop projects. A key in changing the status quo has been the creation of Predictive Modeling Markup Language (PMML), a standard language for creating statistical and data-mining models. It allows a model to be developed using one system, and deployed on another system using a completely different application. Prior to the development of PMML, model conversion was a time-consuming, expensive process.