Train model (Anomaly)
POST {{baseUrl}}/api/:projectId/jobs/train/anomaly/:learnId
Take the output from a DSP block and train an anomaly detection model using K-means. Updates are streamed over the websocket API.
Request Body
{"axes"=>[{"value"=>"<Error: Too many levels of nesting to fake this schema>"}, {"value"=>"<Error: Too many levels of nesting to fake this schema>"}], "clusterCount"=>"<integer>", "minimumConfidenceRating"=>"<number>"}
HEADERS
| Key | Datatype | Required | Description |
|---|---|---|---|
Content-Type | string | ||
Accept | string |
RESPONSES
status: OK
{"id":{"value":"\u003cError: Too many levels of nesting to fake this schema\u003e"}}