PMML Evaluator

Supported pipeline types:

  • Data Collector
The PMML Evaluator processor uses a machine learning model stored in the Predictive Model Markup Language (PMML) format to generate predictions or classifications of data.

With the PMML Evaluator processor, you can create pipelines that predict the existence of known patterns in your data and gain real-time insights. For example, you can design pipelines that detect fraud or needed maintenance as data passes through the pipeline.

The PMML Evaluator processor is available with a paid subscription. For details, contact StreamSets.

To use the PMML Evaluator processor, you first build and train the model with your preferred machine learning technology. You then export the trained model to a PMML document and save that file on the Data Collector machine that runs the pipeline.

When you configure the PMML Evaluator processor, you define the path to the saved PMML document stored on the Data Collector machine. You also define mappings between fields in the record and input fields in the model, and you define the model fields to output and the record field to store the model output.