Package com.azure.ai.anomalydetector.models

Class UnivariateLastDetectionResult

java.lang.Object
com.azure.ai.anomalydetector.models.UnivariateLastDetectionResult
public final class UnivariateLastDetectionResult extends Object
The response of last anomaly detection.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    getExpectedValue()
    Get the expectedValue property: Expected value of the latest point.
    double
    getLowerMargin()
    Get the lowerMargin property: Lower margin of the latest point.
    int
    getPeriod()
    Get the period property: Frequency extracted from the series, zero means no recurrent pattern has been found.
    Double
    getSeverity()
    Get the severity property: The severity score for the last input point.
    int
    getSuggestedWindow()
    Get the suggestedWindow property: Suggested input series points needed for detecting the latest point.
    double
    getUpperMargin()
    Get the upperMargin property: Upper margin of the latest point.
    boolean
    isAnomaly()
    Get the isAnomaly property: Anomaly status of the latest point, true means the latest point is an anomaly either in negative direction or positive direction.
    boolean
    isNegativeAnomaly()
    Get the isNegativeAnomaly property: Anomaly status in negative direction of the latest point.
    boolean
    isPositiveAnomaly()
    Get the isPositiveAnomaly property: Anomaly status in positive direction of the latest point.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Method Details

    • 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.

    • getSuggestedWindow

      public int getSuggestedWindow()
      Get the suggestedWindow property: Suggested input series points needed for detecting the latest point.
      Returns:
      the suggestedWindow value.

    • getExpectedValue

      public double getExpectedValue()
      Get the expectedValue property: Expected value of the latest point.
      Returns:
      the expectedValue value.

    • getUpperMargin

      public double getUpperMargin()
      Get the upperMargin property: Upper margin of the latest point. UpperMargin is used to calculate upperBoundary, which equals to expectedValue + (100 - marginScale)*upperMargin. If the value of latest point is between upperBoundary and lowerBoundary, it should be treated as normal value. By adjusting marginScale value, anomaly status of latest point can be changed.
      Returns:
      the upperMargin value.

    • getLowerMargin

      public double getLowerMargin()
      Get the lowerMargin property: Lower margin of the latest point. LowerMargin is used to calculate lowerBoundary, which equals to expectedValue - (100 - marginScale)*lowerMargin.
      Returns:
      the lowerMargin value.

    • isAnomaly

      public boolean isAnomaly()
      Get the isAnomaly property: Anomaly status of the latest point, true means the latest point is an anomaly either in negative direction or positive direction.
      Returns:
      the isAnomaly value.

    • isNegativeAnomaly

      public boolean isNegativeAnomaly()
      Get the isNegativeAnomaly property: Anomaly status in negative direction of the latest point. True means the latest point is an anomaly and its real value is smaller than the expected one.
      Returns:
      the isNegativeAnomaly value.

    • isPositiveAnomaly

      public boolean isPositiveAnomaly()
      Get the isPositiveAnomaly property: Anomaly status in positive direction of the latest point. True means the latest point is an anomaly and its real value is larger than the expected one.
      Returns:
      the isPositiveAnomaly value.

    • getSeverity

      public Double getSeverity()
      Get the severity property: The severity score for the last 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.