MLeap Evaluator

Data Collector

The MLeap Evaluator processor uses a machine learning model stored in an MLeap bundle to generate evaluations, scoring, or classifications of data.

With the MLeap Evaluator processor, you can create pipelines that produce data-driven insights in real time. For example, you can design pipelines that detect fraudulent transactions or that perform natural language processing as data passes through the pipeline.

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

When you configure the MLeap Evaluator processor, you define the path to the saved MLeap bundle 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.