MODULE REFERENCE

rolling_window

anomx.models.forecasting.rolling_window

Forecasting-based anomaly model.

RollingWindowForecastModel

RollingWindowForecastModel(config: dict[str, Any] | None = None)

Estimate expected values from a rolling window and score residuals.

Signature parameters
Parameter	Type	Default
`config`	`dict[str, Any] \| None`	`None`

component_keyattribute

component_key = 'rolling_window_forecast'

component_iconattribute

component_icon = 'TrendUp01'

signatureattribute

signature = ModelSignature(structures={DataStructure.TEMPORAL_SEQUENCE, DataStructure.SEQUENCE}, modalities={Modality.NUMERIC})

component_nameattribute

component_name = 'Rolling Window Forecast'

component_default_configattribute

component_default_config = {'feature_columns': [], 'min_periods': 3, 'window': 24}

component_config_schemaattribute

component_config_schema = {'feature_columns': {'type': 'array'}, 'min_periods': {'type': 'integer'}, 'window': {'type': 'integer'}}

fitmethod

fit(data: Any) -> None

Signature parameters
Parameter	Type	Default
`data`	`Any`	`required`

Returns None

predictmethod

predict(data: Any) -> pd.DataFrame

Signature parameters
Parameter	Type	Default
`data`	`Any`	`required`

Returns pd.DataFrame

savemethod

save(path: str) -> None

Signature parameters
Parameter	Type	Default
`path`	`str`	`required`

Returns None

loadmethod

load(path: str) -> RollingWindowForecastModel

Signature parameters
Parameter	Type	Default
`path`	`str`	`required`

Returns RollingWindowForecastModel