saealib.AccuracyEvaluator#

class saealib.AccuracyEvaluator(metrics=None)[ソース]#

ベースクラス: ABC

Abstract base for surrogate accuracy evaluators.

Subclasses implement different evaluation strategies (k-fold CV, LOO, held-out). All share the same evaluate() interface so they can be injected into GlobalSurrogateManager interchangeably.

パラメータ:

metrics (list[SurrogateAccuracyMetric] or None) -- Metrics to compute. Defaults to SpearmanCorrelation, RMSE, R2Score.

Methods

__init__

evaluate

Compute accuracy metrics for surrogate on the given training data.

Method Details

AccuracyEvaluator.__init__(metrics=None)[ソース]#
パラメータ:

metrics (list[SurrogateAccuracyMetric] | None)

abstractmethod AccuracyEvaluator.evaluate(surrogate, train_x, train_y)[ソース]#

Compute accuracy metrics for surrogate on the given training data.

パラメータ:

  • surrogate (Surrogate) -- Surrogate instance to evaluate.

  • train_x (np.ndarray) -- Training inputs. shape: (n_samples, n_features)

  • train_y (np.ndarray) -- Training targets. shape: (n_samples, n_obj)

戻り値の型:

SurrogateAccuracy