Machine Learning

Real-time digital twin models can leverage machine learning (ML) and statistical analysis algorithms to detect spikes and trends in properties maintained by real-time digital twin instances. They also can use ML with supervised learning to detect anomalies in sets of properties. ScaleOut Software’s implementation of machine learning makes use of Microsoft’s ML.NET library. User can incorporate ML algorithms into real-time digital twins with the ScaleOut Model Development Tool™; no code development is required.

This topic describes the ML techniques currently available for use in ScaleOut Digital Twins™.

Contents:

• Overview of ML Techniques
• Spike and Trend Change Detection
• Anomaly Detection with Supervised Learning