This workflow trains an auto-regressive model for anomaly detection: - Filter the data to training data covering only normal functioning - Visualize the amplitude values on two selected frequency bands - 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
Used extensions & nodes
Created with KNIME Analytics Platform version 4.6.1
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