Isolation Forest Anomaly Detection Model
The Isolation Forest Anomaly Detection Model for IBM® Maximo® Asset Monitor applies the open source model and includes specialized IoT models, analysis notebooks, functions, and dashboards for Anomaly Detection.
The use case here is to detect anomalies within a Maximo Asset Monitor dataset using a scikit-learn model, which is externally hosted in a Watson Machine Learning service. Anomalies are able to be visualized and metric correlations between anomalies via time-series graphs.
When the data scientist has trained and tested this model with their asset , they will understand how to:
- Load asset data into Monitor
- Forward data to external services via REST HTTP call.
- Build a dashboard using Maximo Asset Monitor to monitor, visualize, and analyze IOT asset data and Anomalies
- Generate alerts when certain results are received.
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Product is offered as a free, non-supported example of an open source model packaged for Maximo Asset Monitor. Please submit any questions as a direct message to AI Applications Store, or use site resources for help.
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