Aggregation strategy

smac.multi_objective.aggregation_strategy

MeanAggregationStrategy

MeanAggregationStrategy(
    scenario: Scenario,
    objective_weights: list[float] | None = None,
)

Bases: AbstractMultiObjectiveAlgorithm

A class to mean-aggregate multi-objective costs to a single cost.

PARAMETER	DESCRIPTION
scenario	TYPE: Scenario
objective_weights	Weights for an weighted average. Must be of the same length as the number of objectives. TYPE: list[float] | None, defaults to None DEFAULT: None

Source code in smac/multi_objective/aggregation_strategy.py

def __init__(
    self,
    scenario: Scenario,
    objective_weights: list[float] | None = None,
):
    super(MeanAggregationStrategy, self).__init__()

    if objective_weights is not None and scenario.count_objectives() != len(objective_weights):
        raise ValueError("Number of objectives and number of weights must be equal.")

    self._objective_weights = objective_weights

meta property

meta: dict[str, Any]

Returns the meta data of the created object.

update_on_iteration_start

update_on_iteration_start() -> None

Update the internal state on start of each SMBO iteration.

Source code in smac/multi_objective/abstract_multi_objective_algorithm.py

def update_on_iteration_start(self) -> None:
    """Update the internal state on start of each SMBO iteration."""
    pass