MODULE REFERENCE

constant

anomx.models.forecasting.constant

Deliberately trivial baseline model used to exercise the pipeline system.

ConstantBaselineModel

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

Bases: NormalityModel, Predictive

Predict the per-feature training mean for every observation.

The model exists to validate orchestration end to end: it trains instantly, predicts deterministically, and produces residual-style model_score output that any scorer can consume.

Signature parameters
ParameterTypeDefault
configdict[str, Any] | NoneNone

Members

component_keyattribute
component_key = 'constant_baseline'
component_iconattribute
signatureattribute
signature = ModelSignature(structures={DataStructure.TABULAR, DataStructure.TEMPORAL_SEQUENCE}, modalities={Modality.NUMERIC})
component_nameattribute
component_name = 'Constant Baseline'
component_default_configattribute
component_default_config = {'feature_columns': []}
component_config_schemaattribute
component_config_schema = {'feature_columns': {'type': 'array'}}
capabilitiesattribute
capabilities: ClassVar[ComponentCapabilities] = ComponentCapabilities(supports_sequences=True, supports_streaming=True, streaming_inference=True)
fitmethod
fit(data: Any) -> None
Signature parameters
ParameterTypeDefault
dataAnyrequired

Returns None

predictmethod
predict(data: Any) -> pd.DataFrame
Signature parameters
ParameterTypeDefault
dataAnyrequired

Returns pd.DataFrame

savemethod
save(path: str) -> None
Signature parameters
ParameterTypeDefault
pathstrrequired

Returns None

loadmethod
load(path: str) -> ConstantBaselineModel
Signature parameters
ParameterTypeDefault
pathstrrequired

Returns ConstantBaselineModel