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UnivariateEntireDetectionResult Class

  • Reference
Package:
com.azure.ai.anomalydetector.models
Maven Artifact:
com.azure:azure-ai-anomalydetector:3.0.0-beta.5
  • java.lang.Object
    • com.azure.ai.anomalydetector.models.UnivariateEntireDetectionResult

public final class UnivariateEntireDetectionResult

The response of entire anomaly detection.

Method Summary

Modifier and Type Method and Description
List<Double> getExpectedValues()

Get the expectedValues property: ExpectedValues contain expected value for each input point.
List<Boolean> getIsAnomaly()

Get the isAnomaly property: IsAnomaly contains anomaly properties for each input point.
List<Boolean> getIsNegativeAnomaly()

Get the isNegativeAnomaly property: IsNegativeAnomaly contains anomaly status in negative direction for each input point.
List<Boolean> getIsPositiveAnomaly()

Get the isPositiveAnomaly property: IsPositiveAnomaly contain anomaly status in positive direction for each input point.
List<Double> getLowerMargins()

Get the lowerMargins property: LowerMargins contain lower margin of each input point.
int getPeriod()

Get the period property: Frequency extracted from the series, zero means no recurrent pattern has been found.
List<Double> getSeverity()

Get the severity property: The severity score for each input point.
List<Double> getUpperMargins()

Get the upperMargins property: UpperMargins contain upper margin of each input point.

Methods inherited from java.lang.Object

clone equals finalize getClass hashCode notify notifyAll toString wait wait wait

Method Details

getExpectedValues

public List getExpectedValues()

Get the expectedValues property: ExpectedValues contain expected value for each input point. The index of the array is consistent with the input series.

Returns:

the expectedValues value.

getIsAnomaly

public List getIsAnomaly()

Get the isAnomaly property: IsAnomaly contains anomaly properties for each input point. True means an anomaly either negative or positive has been detected. The index of the array is consistent with the input series.

Returns:

the isAnomaly value.

getIsNegativeAnomaly

public List getIsNegativeAnomaly()

Get the isNegativeAnomaly property: IsNegativeAnomaly contains anomaly status in negative direction for each input point. True means a negative anomaly has been detected. A negative anomaly means the point is detected as an anomaly and its real value is smaller than the expected one. The index of the array is consistent with the input series.

Returns:

the isNegativeAnomaly value.

getIsPositiveAnomaly

public List getIsPositiveAnomaly()

Get the isPositiveAnomaly property: IsPositiveAnomaly contain anomaly status in positive direction for each input point. True means a positive anomaly has been detected. A positive anomaly means the point is detected as an anomaly and its real value is larger than the expected one. The index of the array is consistent with the input series.

Returns:

the isPositiveAnomaly value.

getLowerMargins

public List getLowerMargins()

Get the lowerMargins property: LowerMargins contain lower margin of each input point. LowerMargin is used to calculate lowerBoundary, which equals to expectedValue - (100 - marginScale)*lowerMargin. Points between the boundary can be marked as normal ones in client side. The index of the array is consistent with the input series.

Returns:

the lowerMargins value.

getPeriod

public int getPeriod()

Get the period property: Frequency extracted from the series, zero means no recurrent pattern has been found.

Returns:

the period value.

getSeverity

public List getSeverity()

Get the severity property: The severity score for each input point. The larger the value is, the more sever the anomaly is. For normal points, the "severity" is always 0.

Returns:

the severity value.

getUpperMargins

public List getUpperMargins()

Get the upperMargins property: UpperMargins contain upper margin of each input point. UpperMargin is used to calculate upperBoundary, which equals to expectedValue + (100 - marginScale)*upperMargin. Anomalies in response can be filtered by upperBoundary and lowerBoundary. By adjusting marginScale value, less significant anomalies can be filtered in client side. The index of the array is consistent with the input series.

Returns:

the upperMargins value.

Applies to