vopy.datasets
Datasets for maximization problems.
References:
Liao, Li, Yang, Zhang, Li. Multiobjective optimization for crash safety design of vehicles using stepwise regression model. Structural and Multidisciplinary Optimization, 2008.
Tanabe, Ishibuchi. An easy-to-use real-world multi-objective optimization problem suite. Applied Soft Computing, 2020.
Zuluaga, Milder, Püschel. Computer generation of streaming sorting networks. Design Automation Conference, 2012.
Grari, Laugel, Hashimoto, Lamprier, Detyniecki. On the Fairness ROAD: Robust Optimization for Adversarial Debiasing. International Conference on Learning Representations, 2024.
- class vopy.datasets.dataset.Dataset
Abstract base class for datasets that handles min-max scaling of input and standardization of output. Any class inheriting from this class should implement the following attributes:
_in_dim
:int
_out_dim
:int
_cardinality
:int
- class vopy.datasets.dataset.DiscBrake
Disc brake optimization balancing mass and stopping time. Based on [Tanabe2020]. Both objectives are negated.
_in_dim = 4
_out_dim = 2
_cardinality = 128
- class vopy.datasets.dataset.Fairness
Dataset for optimizing fairness in machine learning. Dataset consists of possible hyperparameter selections of ROAD approach on a neural network architecture. The reward vector represents the trade-off between global disparate impact and global accuracy. See [Grari2024]. Disparate impact is negated.
_in_dim = 2
_out_dim = 2
_cardinality = 200
- class vopy.datasets.dataset.SNW
Dataset for optimizing sorting network configurations in computational hardware design. The reward vector represents the trade-off between throughput and hardware area. The area is negated to maximize it. See [Zuluaga2012].
_in_dim = 3
_out_dim = 2
_cardinality = 206
- class vopy.datasets.dataset.Test
A miniature DiscBrake dataset variant for using in testing.
_in_dim = 4
_out_dim = 2
_cardinality = 32
- class vopy.datasets.dataset.VehicleSafety
Vehicle structure optimization dataset for enhancing crashworthiness. The reward vector includes weight, acceleration, and toe-board intrusion. See [Liao2008] and [Tanabe2020].
_in_dim = 5
_out_dim = 3
_cardinality = 500
- vopy.datasets.dataset.get_dataset_instance(dataset_name: str) Dataset
Returns an instance of the dataset class corresponding to the given dataset name. If the dataset name is not recognized, a ValueError is raised.
- Parameters:
dataset_name (str) – Name of the dataset class to be instantiated.
- Returns:
Instance of the dataset class.
- Return type: