paref.moo_algorithms.two_dimensional.fill_gaps_of_pareto_front_2d#
Classes
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Fill gaps of Pareto front in two dimensions |
- class paref.moo_algorithms.two_dimensional.fill_gaps_of_pareto_front_2d.FillGapsOfParetoFront2D(max_iter_minimizer: int = 500, training_iter: int = 2000, learning_rate: float = 0.05, min_distance_to_evaluated_points: float = 0.02)[source]#
Bases:
GPRMinimizerFill gaps of Pareto front in two dimensions
Use this algorithm if you want to fill the gaps between the currently found Pareto front (Pareto front of the evaluations).
Initialize the algorithms hyperparameters
- Parameters:
max_iter_minimizer (int default 100) – maximum number of iterations of the differential evolution algorithm
training_iter (int default 2000) – maximum training iterations of the GPR(s)
learning_rate (float default 0.05) – learning rate of the training of the GPR(s)
min_required_evaluations (int default 20) – minimum number of evaluations required for the training (must be greater or equal than 20)
min_distance_to_evaluated_points (float default 2e-2) – required minimum distance to already evaluated points
- property sequence_of_pareto_reflections: SequenceParetoReflections#
- property supported_codomain_dimensions: int#