gemseo.mlearning.regression.algos.thin_plate_spline_settings module#
Settings of the thin plate spline (TPS) regressor.
- Settings TPSRegressor_Settings(*, transformer=None, parameters=None, input_names=(), output_names=(), function=Function.THIN_PLATE, der_function=None, epsilon=None, smooth=0.0, norm='euclidean')[source]#
Bases:
RBFRegressor_Settings
The settings of the thin plate spline (TPS) 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:
input_names (Sequence[str]) --
By default it is set to ().
output_names (Sequence[str]) --
By default it is set to ().
function (Literal[Function.THIN_PLATE]) --
By default it is set to "thin_plate".
der_function (Annotated[Callable[[_NDArrayPydantic[Any, dtype[_ScalarType_co]]], _NDArrayPydantic[Any, dtype[_ScalarType_co]]], WithJsonSchema(json_schema={}, mode=None)] | None)
epsilon (float | None)
smooth (float) --
By default it is set to 0.0.
norm (str | Annotated[Callable[[_NDArrayPydantic[Any, dtype[_ScalarType_co]], _NDArrayPydantic[Any, dtype[_ScalarType_co]]], float], WithJsonSchema(json_schema={}, mode=None)]) --
By default it is set to "euclidean".
- Return type:
None
- function: Literal[Function.THIN_PLATE] = Function.THIN_PLATE#
The thin plate radial basis function for \(r^2\log(r)\).