ertk.sklearn.models.SkWrapperConfig

class ertk.sklearn.models.SkWrapperConfig(kwargs: dict[str, typing.Any] = <factory>, transform: str | None = 'std', transform_kwargs: dict[str, typing.Any] = <factory>, param_grid: dict[str, typing.Any] = <factory>, param_grid_path: str | None = None)

Bases: SkModelConfig

Configuration for a scikit-learn model wrapper.

__init__(kwargs: dict[str, typing.Any] = <factory>, transform: str | None = 'std', transform_kwargs: dict[str, typing.Any] = <factory>, param_grid: dict[str, typing.Any] = <factory>, param_grid_path: str | None = None) → None

Methods

Inherited Methods

__init__([kwargs, transform, ...])
default()	Create default config.
from_config(config)	Create config object from any compatible config.
from_file(path)	Create config from YAML file and optionlly override some values.
merge_with_args(args)	Merge config with command-line arguments.
merge_with_config(config)	Merge other config into this config.
to_dictconfig()	Convert config to DictConfig.
to_file(path)	Write config to YAML file.
to_string()	Generate YAML string representation of config.

Attributes

kind	The name of the model to wrap.
param_grid_path	The path to a YAML file containing the parameter grid to use for grid search.
transform	The name of the transform to use.

kind: str = '???'

The name of the model to wrap.