Anomaly Detection. Time Series AR Training
This workflow trains an auto-regressive model for anomaly detection:
- Filter the data to training data covering only normal functioning
- Loop over each frequency column at a time
- Train an auto-regressive model using 10 past values as predictors
- Calculate in-sample prediction error statistics
- Save the model and prediction error statistics for deployment
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
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