Scaling#

class pymc_marketing.mmm.scaling.Scaling(**data)[source]#

Scaling configuration for the MMM.

Examples

Scale the target variable by max value by group of ‘DMA’

from pymc_marketing.mmm.multidimensional import Scaling

scaling = Scaling(**{
    "target": {
        "method": "max",
        # Exclude 'DMA' from dims here.
        "dims": (),
    },
})

Methods

`Scaling.__init__`(**data)	Create a new model by parsing and validating input data from keyword arguments.
`Scaling.construct`([_fields_set])
`Scaling.copy`(*[, include, exclude, update, deep])	Returns a copy of the model.
`Scaling.dict`(*[, include, exclude, ...])
`Scaling.from_orm`(obj)
`Scaling.json`(*[, include, exclude, ...])
`Scaling.model_construct`([_fields_set])	Creates a new instance of the `Model` class with validated data.
`Scaling.model_copy`(*[, update, deep])	!!! abstract "Usage Documentation"
`Scaling.model_dump`(*[, mode, include, ...])	!!! abstract "Usage Documentation"
`Scaling.model_dump_json`(*[, indent, ...])	!!! abstract "Usage Documentation"
`Scaling.model_json_schema`([by_alias, ...])	Generates a JSON schema for a model class.
`Scaling.model_parametrized_name`(params)	Compute the class name for parametrizations of generic classes.
`Scaling.model_post_init`(context, /)	Override this method to perform additional initialization after `__init__` and `model_construct`.
`Scaling.model_rebuild`(*[, force, ...])	Try to rebuild the pydantic-core schema for the model.
`Scaling.model_validate`(obj, *[, strict, ...])	Validate a pydantic model instance.
`Scaling.model_validate_json`(json_data, *[, ...])	!!! abstract "Usage Documentation"
`Scaling.model_validate_strings`(obj, *[, ...])	Validate the given object with string data against the Pydantic model.
`Scaling.parse_file`(path, *[, content_type, ...])
`Scaling.parse_obj`(obj)
`Scaling.parse_raw`(b, *[, content_type, ...])
`Scaling.schema`([by_alias, ref_template])
`Scaling.schema_json`(*[, by_alias, ref_template])
`Scaling.update_forward_refs`(**localns)
`Scaling.validate`(value)

Attributes

`model_computed_fields`
`model_config`	Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].
`model_extra`	Get extra fields set during validation.
`model_fields`
`model_fields_set`	Returns the set of fields that have been explicitly set on this model instance.
`target`
`channel`