Flogo Machine Learning Isolation Forest Anomaly Detection

This sample uses TIBCO Flogo in tandem with Python Scikit-learn open-source machine learning library to demonstrate Artificial Intelligence Machine Learning (AI-ML) in a real-time eventing scenario deployable into the TIBCO Platform. 

The sample demonstrate 

- Few-shot training to train Machine Learning models.
- Training and inferencing can be done in real-time eventing scenario.
- Self healing are employed in the data set in case the norm shifts.
- TIBCO Platform can be used for AI-ML use-cases.

The use-case in this sample is the monitoring of temperature in a machine inside a manufacturing plant. The temperature of the machine can vary depending on the geographic location and the environment that it is operating in. Thereby, it is hard to pinpoint what would be the expected temperature range. However, during operation, the temperature is expected to be relatively stable.
