LastDetectResponse Class

The response of last anomaly detection.

All required parameters must be populated in order to send to Azure.

Inheritance

Model

LastDetectResponse

Constructor

LastDetectResponse(*, period: int, suggested_window: int, expected_value: float, upper_margin: float, lower_margin: float, is_anomaly: bool, is_negative_anomaly: bool, is_positive_anomaly: bool, severity: Optional[float] = None, **kwargs)

Variables

period

int

Required. Frequency extracted from the series, zero means no recurrent pattern has been found.

suggested_window

int

Required. Suggested input series points needed for detecting the latest point.

expected_value

float

Required. Expected value of the latest point.

upper_margin

float

Required. 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.

lower_margin

float

Required. Lower margin of the latest point. LowerMargin is used to calculate lowerBoundary, which equals to expectedValue - (100 - marginScale)*lowerMargin.

is_anomaly

bool

Required. Anomaly status of the latest point, true means the latest point is an anomaly either in negative direction or positive direction.

is_negative_anomaly

bool

Required. 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.

is_positive_anomaly

bool

Required. 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.

severity

float

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.