Hyper-Parameter Optimization in Support Vector Machine on Unbalanced Datasets Using Genetic Algorithms

DOI10.1007/978-3-030-95380-5_4zbMath1524.68278OpenAlexW4285125811MaRDI QIDQ6165043

Domenico Conforti, Maria Carmela Groccia, Rosita Guido

Publication date: 31 July 2023

Published in: AIRO Springer Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-95380-5_4

zbMATH Keywords

genetic algorithmsmachine learningsupport vector machinehyper-parameter optimizationNSGA IIcost-sensitive approach

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)

Cites Work

• Kernel methods in machine learning
• A hybrid genetic approach for solving an integrated multi-objective operating room planning and scheduling problem
• Support-vector networks
• Machine Learning: ECML 2004
• Paradoxes of fuzzy logic, revisited
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