DataDerivedScaling

pydantic model pymc_marketing.mmm.scaling.DataDerivedScaling

Scale by a statistic of the data, computed at fit time.

Examples

Max-absolute scaling (default behaviour):

DataDerivedScaling(method="max", dims=())

Mean-absolute scaling across a custom dimension:

DataDerivedScaling(method="mean", dims=("country",))

Methods

DataDerivedScaling.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
DataDerivedScaling.from_dict(data)	Reconstruct from a dict via Pydantic model_validate.
DataDerivedScaling.scaling_description()	Human-readable summary of the scaling strategy.
DataDerivedScaling.to_dict([_orig])	Serialize to a dict via Pydantic model_dump.

field dims: str | tuple[str, ...] [Required]

The dimensions to perform the operation through ("date" is always included implicitly).

field method: Literal['max', 'mean'] [Required]

The scaling method.