saealib.Decomposition

class saealib.Decomposition

ベースクラス: ABC

Abstract base for scalarization (decomposition) functions.

A Decomposition converts a batch of objective vectors into a single scalar score per vector. Smaller scores are always better (minimization convention). The caller is responsible for applying any direction transform before passing f (i.e., f should already be in a minimization frame where smaller = better for every objective).

パラメータ:

• f (np.ndarray) -- Objective matrix, shape (N, n_obj). All objectives are assumed to be in minimization direction (direction transform applied by the caller).

• weights (np.ndarray) -- Non-negative weight vector, shape (n_obj,).

• ideal_point (np.ndarray) -- Reference minimum per objective, shape (n_obj,). For methods that do not use the ideal point (e.g. WeightedSumDecomposition), this argument is accepted but ignored.

戻り値:

Scalar scores, shape (N,). Lower is better.

戻り値の型:

np.ndarray

Methods

__init__
aggregate	Scalarize a batch of objective vectors.
contract	Return the decomposition contract.

Method Details

Decomposition.__init__()

abstractmethod Decomposition.aggregate(f, weights, ideal_point)

Scalarize a batch of objective vectors.

パラメータ:

• f (np.ndarray) -- Objective matrix, shape (N, n_obj). Must be in the minimization frame (all objectives: smaller = better).

• weights (np.ndarray) -- Non-negative weight vector, shape (n_obj,).

• ideal_point (np.ndarray) -- Reference minimum per objective, shape (n_obj,).

戻り値:

Scalar scores, shape (N,). Lower is better.

戻り値の型:

np.ndarray

Decomposition.contract()

Return the decomposition contract.

戻り値の型:

ComponentContract