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results found
Imbalanced binary classification is a common issue in serious contexts when rare events have practical effects. Traditional cost-sensitive strategies improve minority identification, but they frequent...
binary classification
imbalanced dataset
cost sensitivity
features selection
mathematical programming
Superconducting magnets for particle accelerators are particularly challenging to design because they involve a large number of coupled physical phenomena and the management of complex datasets. Artif...
Superconducting Magnets
Artificial Intelligence
Machine Learning
Evolutionary Computation
Topology Optimisation
Quench Anomaly detection
SinoXiv