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detect_univariate_entire_series

Creates, updates, deletes, gets or lists a detect_univariate_entire_series resource.

Overview​

Namedetect_univariate_entire_series
TypeResource
Idazure.ai_anomaly_detector.detect_univariate_entire_series

Fields​

The following fields are returned by SELECT queries:

SELECT not supported for this resource, use SHOW METHODS to view available operations for the resource.

Methods​

The following methods are available for this resource:

NameAccessible byRequired ParamsOptional ParamsDescription
detect_univariate_entire_seriesexecendpoint, api_version, seriesDetect anomalies for the entire series in batch. This operation generates a model with an entire series, each point is detected with the same model. With this method, points before and after a certain point are used to determine whether it is an anomaly. The entire detection can give user an overall status of the time series.

Parameters​

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

NameDatatypeDescription
api_versionstringThe service endpoint host (no scheme), e.g. myaccount.table.cosmos.azure.com:443 - value of the client ApiVersion parameter. (default: )
endpointstringThe service endpoint host (no scheme), e.g. myaccount.table.cosmos.azure.com:443 - value of the client Endpoint parameter. (default: )

Lifecycle Methods​

Detect anomalies for the entire series in batch. This operation generates a model with an entire series, each point is detected with the same model. With this method, points before and after a certain point are used to determine whether it is an anomaly. The entire detection can give user an overall status of the time series.

EXEC azure.ai_anomaly_detector.detect_univariate_entire_series.detect_univariate_entire_series
@endpoint='{{ endpoint }}' --required,
@api_version='{{ api_version }}' --required
@@json=
'{
"series": "{{ series }}",
"granularity": "{{ granularity }}",
"customInterval": {{ customInterval }},
"period": {{ period }},
"maxAnomalyRatio": {{ maxAnomalyRatio }},
"sensitivity": {{ sensitivity }},
"imputeMode": "{{ imputeMode }}",
"imputeFixedValue": {{ imputeFixedValue }}
}'
;