saealib.IndividualBasedStrategy#

class saealib.IndividualBasedStrategy(evaluation_ratio=0.1)[source]#

Bases: OptimizationStrategy

Individual-based strategy.

Parameters:

evaluation_ratio (float)

Methods

__init__

Initialize IndividualBasedStrategy.

build_graph

Build the canonical individual-based strategy graph.

build_pipeline

Return the strategy's high-level Pipeline description.

contract

Return the strategy contract.

step

Score all offspring with the surrogate, then true-evaluate the top fraction.

Method Details

IndividualBasedStrategy.__init__(evaluation_ratio=0.1)[source]#

Initialize IndividualBasedStrategy.

Parameters:

evaluation_ratio (float) – Ratio of offspring selected for true objective evaluation. The top evaluation_ratio fraction of offspring are evaluated with the real objective function; the rest are discarded after surrogate scoring. The number of neighbors for local surrogate fitting is now configured on the SurrogateManager (e.g. LocalSurrogateManager).

IndividualBasedStrategy.build_graph(provider)[source]#

Build the canonical individual-based strategy graph.

Parameters:

provider (ComponentProvider)

Return type:

ComponentGraph

IndividualBasedStrategy.build_pipeline(provider)#

Return the strategy’s high-level Pipeline description.

Parameters:

provider (ComponentProvider)

Return type:

Pipeline

IndividualBasedStrategy.contract()#

Return the strategy contract.

Return type:

ComponentContract

IndividualBasedStrategy.step(ctx, provider)[source]#

Score all offspring with the surrogate, then true-evaluate the top fraction.

Rebuilds the pipeline each call so component/parameter changes take effect immediately.

Parameters:
  • ctx (OptimizationState) – Current optimization context.

  • provider (ComponentProvider) – Component provider.

Return type:

OptimizationState