SampleWeightConfig

class openstef_models.transforms.general.sample_weighter.SampleWeightConfig(**data: Any) → None

Bases: BaseConfig

Configuration for sample weighting parameters.

Groups all parameters that control how training samples are weighted. Supports two methods: exponential (magnitude-based) and inverse_frequency (rarity-based).

Parameters:

data (Any)

method: Literal['exponential', 'inverse_frequency']

weight_scale_percentile: int

weight_exponent: float

n_bins: int

dampening_exponent: float

weight_floor: float

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': False, 'extra': 'ignore', 'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].