autointent.configs.DataConfig#

class autointent.configs.DataConfig(/, **data)#

Bases: pydantic.BaseModel

Configuration for the data used in the optimization process.

Parameters:

data (Any)

model_config#

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

scheme: autointent.custom_types.ValidationScheme = None#

Hold-out or cross-validation.

n_folds: pydantic.PositiveInt = None#

Number of folds in cross-validation.

validation_size: autointent.custom_types.FloatFromZeroToOne = None#

Fraction of train samples to allocate for validation (if input dataset doesn’t contain validation split).

separation_ratio: autointent.custom_types.FloatFromZeroToOne | None = None#

Set to float to prevent data leak between scoring and decision nodes.