UnivariateLastDetectionResult Class

Definition

Namespace:

Azure.AI.AnomalyDetector

Assembly:

Azure.AI.AnomalyDetector.dll

Package:

Azure.AI.AnomalyDetector v3.0.0-preview.7

Source:

UnivariateLastDetectionResult.cs

Response of the last anomaly detection.

public class UnivariateLastDetectionResult

type UnivariateLastDetectionResult = class

Public Class UnivariateLastDetectionResult

Inheritance

Object

UnivariateLastDetectionResult

Properties

ExpectedValue	Expected value of the latest point.
IsAnomaly	Anomaly status of the latest point. True means the latest point is an anomaly, either in the negative direction or in the positive direction.
IsNegativeAnomaly	Anomaly status of the latest point in a negative direction. True means the latest point is an anomaly and its real value is smaller than the expected one.
IsPositiveAnomaly	Anomaly status of the latest point in a positive direction. True means the latest point is an anomaly and its real value is larger than the expected one.
LowerMargin	Lower margin of the latest point. LowerMargin is used to calculate lowerBoundary, which is equal to expectedValue - (100 - marginScale)*lowerMargin.
Period	Frequency extracted from the series. Zero means no recurrent pattern has been found.
Severity	Severity score for the last input point. The larger the value is, the more severe the anomaly is. For normal points, the severity is always 0.
SuggestedWindow	Suggested input series points needed for detecting the latest point.
UpperMargin	Upper margin of the latest point. UpperMargin is used to calculate upperBoundary, which is equal to expectedValue + (100 - marginScale)*upperMargin. If the value of latest point is between upperBoundary and lowerBoundary, it should be treated as a normal value. Adjusting the marginScale value enables the anomaly status of the latest point to be changed.