svm module¶
Support vector machine for regression.
The support vector machine model relies on the SVR
class of sklearn
.
- class gemseo_mlearning.regression.svm.SVMRegressor(data, transformer=None, input_names=None, output_names=None, kernel='rbf', **parameters)[source]
Bases:
MLRegressionAlgo
Support vector machine regressor.
- Parameters:
data (Dataset) – The learning dataset.
transformer (Mapping[str, TransformerType] | None) – The strategies to transform the variables. The values are instances of
Transformer
while the keys are the names of either the variables or the groups of variables, e.g."inputs"
or"outputs"
in the case of the regression algorithms. If a group is specified, theTransformer
will be applied to all the variables of this group. IfIDENTITY
, do not transform the variables.input_names (Iterable[str] | None) – The names of the input variables. If
None
, consider all the input variables of the learning dataset.output_names (Iterable[str] | None) – The names of the output variables. If
None
, consider all the output variables of the learning dataset.kernel (str) –
The kernel type to be used.
By default it is set to “rbf”.
**parameters (Any) – The parameters of the machine learning algorithm.
- Raises:
ValueError – When both the variable and the group it belongs to have a transformer.
- LIBRARY: Final[str] = 'scikit-learn'
The name of the library of the wrapped machine learning algorithm.
- SHORT_ALGO_NAME: ClassVar[str] = 'SVMRegression'
The short name of the machine learning algorithm, often an acronym.
Typically used for composite names, e.g.
f"{algo.SHORT_ALGO_NAME}_{dataset.name}"
orf"{algo.SHORT_ALGO_NAME}_{discipline.name}"
.
- algo: Any
The interfaced machine learning algorithm.
- learning_set: IODataset
The learning dataset.
- transformer: dict[str, Transformer]
The strategies to transform the variables, if any.
The values are instances of
Transformer
while the keys are the names of either the variables or the groups of variables, e.g. “inputs” or “outputs” in the case of the regression algorithms. If a group is specified, theTransformer
will be applied to all the variables of this group.