Optimized feature subset selection via simulated annealing

Today's article comes from the Machine Learning Science and Technology journal. The authors are Martinez-Garcia et al., from Instituto de Fisica Fundamental, in Spain. In this paper, they're debuting SA-FDR: an algorithm that uses simulated annealing to search through the space of possible feature subsets, optimizing for something called the Fisher Discriminant Ratio.

DOI: 10.1088/2632-2153/ae20ed

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