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UnivariateLastDetectionResult Class

  • Reference

The response of last anomaly detection.

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

Inheritance
azure.ai.anomalydetector._model_base.Model
UnivariateLastDetectionResult

Constructor

UnivariateLastDetectionResult(*args: Any, **kwargs: Any)

Variables

Name Description
period
int

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

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

Expected value of the latest point. Required.
upper_margin
float

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. Required.
lower_margin
float

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

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

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. Required.
is_positive_anomaly
bool

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. Required.
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.

Methods

clear
copy
get
items
keys
pop
popitem
setdefault
update
values

clear 

clear() -> None

copy 

copy()

get 

get(key: str, default: Any = None) -> Any

Parameters

Name Description
key
Required
default
Default value: None

items 

items() -> ItemsView

keys 

keys() -> KeysView

pop 

pop(key: ~typing.Any, default: ~typing.Any = <object object>) -> Any

Parameters

Name Description
key
Required
default

popitem 

popitem() -> Tuple[str, Any]

setdefault 

setdefault(key: ~typing.Any, default: ~typing.Any = <object object>) -> Any

Parameters

Name Description
key
Required
default

update 

update(*args: Any, **kwargs: Any) -> None

values 

values() -> ValuesView

Attributes

expected_value

Expected value of the latest point. Required.

expected_value: float

is_anomaly

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

is_anomaly: bool

is_negative_anomaly

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. Required.

is_negative_anomaly: bool

is_positive_anomaly

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. Required.

is_positive_anomaly: bool

lower_margin

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

lower_margin: float

period

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

period: int

severity

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.

severity: float | None

suggested_window

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

suggested_window: int

upper_margin

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. Required.

upper_margin: float