smac.model.multi_objective_model¶
Classes¶
|
Wrapper for the surrogate model to predict multiple objectives. |
Interfaces¶
- class smac.model.multi_objective_model.MultiObjectiveModel(models, objectives, seed=0)[source]¶
Bases:
AbstractModel
Wrapper for the surrogate model to predict multiple objectives.
- Parameters:
models (AbstractModel | list[AbstractModel]) – Which model should be used. If it is a list, then it must provide as many models as objectives. If it is a single model only, the model is used for all objectives.
objectives (list[str]) – Which objectives should be used.
seed (int)
- property models: list[AbstractModel]¶
The internally used surrogate models.
- predict_marginalized(X)[source]¶
Predicts mean and variance marginalized over all instances.
Warning
The input data must not include any features.
- Parameters:
X (np.ndarray [#samples, #hyperparameters]) – Input data points.
- Return type:
tuple
[ndarray
,ndarray
]- Returns:
means (np.ndarray [#samples, 1]) – The predictive mean.
vars (np.ndarray [#samples, 1]) – The predictive variance.