UnivariateLastDetectionResult Class
Definition
Important
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Response of the last anomaly detection.
public class UnivariateLastDetectionResulttype UnivariateLastDetectionResult = classPublic Class UnivariateLastDetectionResult- Inheritance
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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. |
