Stochastic Local Search for Efficient Hybrid Feature Selection
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https://hdl.handle.net/11250/2990171Utgivelsesdato
2021Metadata
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Originalversjon
10.1145/3449726.3459438Sammendrag
There is a need to study not only accuracy but also computational cost in machine learning. Focusing on both accuracy and computational cost of feature selection, we develop and test stochastic local search (SLS) heuristics for hybrid feature selection.