Get an Abnormal Profile by ID

get

/api/metric/AbnormalProfiles/{id}

Gets the abnormal profile that matches the specified ID. Abnormal profiles are used by abnormal thresholds and the Metric Abnormal Threshold Engine.

Request

Path Parameters

There's no request body for this operation.

Back to Top

Response

Supported Media Types

200 Response

Successful operation
Body ()
Root Schema : schema
Match All
Show Source
Nested Schema : SuccessfulGetOperation
Type: object
Show Source
Nested Schema : type
Type: object
Show Source
Nested Schema : data
Type: array
Show Source
Nested Schema : metricAbnormalProfilesRead
Type: object
Show Source
  • Abnormal Profile ID
    Example: 1
  • Name of abnormal profile
    Example: Default Abnormal Profile
  • The degree to which the confidence bands smooth a weighted average (more weight being given to recent observations, less to older observations). Values are from >0 to 1. The closer to 1 the Alpha value becomes, the closer the predicted value will be to the weighted average of the last n observations.
    Example: 0.999497
  • The degree to which the smoothing function considers the slope (amount of increase or decrease) of the weighted average of 2 adjacent data points. Values are from >0 to 1. The closer to 1 the Beta value gets, the more the Algorithm will consider the slope of the previous (n-1) data point to the current data point (n) when predicting the next data point (n+1).
    Example: 0.00224
  • Scaling factor, used to influence the width of the confidence bands generated by the Algorithm. Values are between 2 and 3.
    Example: 3
  • Epsilon scaling. Values are >0 to 1.
    Example: 0.492391
  • Used with Window Length by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered "abnormal" and an event will be generated.
    Example: 3
  • The degree to which the smoothing function considers seasonal data when forecasting a data point. Values are >0 to 1. The closer to 1 Gamma gets, the more the Algorithm will weight seasonal patterns when forecasting expected values.
    Example: 0.487092
  • Used with Violation Threshold by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered "abnormal" and an event will be generated. Values are between 0 and 28.
    Example: 5

Default Response

Failed operation
Body ()
Root Schema : schema
Type: object
Show Source
Nested Schema : errors
Type: array
The list of errors reported. Validation errors will be keyed by record field.
Show Source
Nested Schema : items
Type: object
Back to Top