A genetically-optimised artificial life algorithm for complexity-based synthetic dataset generation

Algorithmic evaluation is a vital step in developing new approaches to machine learning and relies on the availability of existing datasets. However, real-world datasets often do not cover the necessary complexity space required to understand an algorithm’s domains of competence. As such, the genera...

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Bibliographic Details
Main Authors: Andrew Houston, Georgina Cosma
Format: Default Article
Published: 2022
Subjects:
Engineering
Information and computing sciences
Mathematical sciences
Synthetic data
Data generation
Complexity theory
Benchmarking
Supervised learning
Online Access:https://hdl.handle.net/2134/21789377.v1
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