Machine Learning

Build 10.5.0.0.40

• Support analysis of device data using scheduled jobs.
  • Schedule batch jobs for processing measurements from devices or device groups against an available model.
  • The job scheduler can be used to trigger one-time or periodic jobs on data captured from devices.
  • The scheduler allows you to map device data to model inputs by providing a mapping tool. Periodic executions of batch jobs can be useful when aggregate information on model’s predictions is required for a desired time period.
• Support for Object Detection using RetinaNet.
• Support for univariate seasonal ARIMA time series models with “conditionalLeastSquares” prediction method.
• Compliance with PMML 4.4 release features:
  • Support for Lag@aggregation=stddev
  • Support for Constant@missing
  • Support for Anomaly Detection release schema