Take the output from a DSP block and train an anomaly detection model using K-means or GMM. Updates are streamed over the websocket API.
Project ID
Learn Block ID, use the impulse functions to retrieve the ID
Which axes (indexes from DSP script) to include in the training set
[0, 11, 22]DEPRECATED, use "thresholds" instead. Minimum confidence rating required before tagging as anomaly
0.3
Number of clusters for K-means, or number of components for GMM
32
If set, skips creating embeddings and measuring memory (used in tests)
List of configurable thresholds for this block.