Train model (Anomaly)
Train model (Anomaly)
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.
POST
Train model (Anomaly)
Documentation Index
Fetch the complete documentation index at: https://docs.edgeimpulse.com/llms.txt
Use this file to discover all available pages before exploring further.
Authorizations
Path Parameters
Project ID
Learn Block ID, use the impulse functions to retrieve the ID
Body
application/json
Which axes (indexes from DSP script) to include in the training set
Example:
[0, 11, 22]DEPRECATED, use "thresholds" instead. Minimum confidence rating required before tagging as anomaly
Example:
0.3
Number of clusters for K-means, or number of components for GMM
Example:
32
If set, skips creating embeddings and measuring memory (used in tests)
List of configurable thresholds for this block.