gemseo.mlearning.regression.algos.svm_settings module

Settings of the SVM regressor.

Settings SVMRegressor_Settings(*, transformer=None, parameters=None, input_names=(), output_names=(), kernel='rbf')

Bases: BaseRegressorSettings

The settings of the SVM regressor.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• transformer (Mapping[str, Any])

• parameters (Mapping[str, Any])

• input_names (Sequence[str]) --

  By default it is set to ().

• output_names (Sequence[str]) --

  By default it is set to ().

• kernel (str | Callable[[], Callable]) --

  By default it is set to "rbf".

Return type:

None

kernel: str | Annotated[Callable, WithJsonSchema({})] = 'rbf'

The name of the kernel or a callable for the SVM.

Examples of names: "linear", "poly", "rbf", "sigmoid", "precomputed".