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What is Improved Binary Aquila Optimization for Feature Selection about?

This paper introduces an Improved Binary Aquila Optimization (IBAO) algorithm for effective feature selection in supervised classification, addressing local optima issues in large datasets. The IBAO algorithm enhances classification accuracy, achieving up to 100% accuracy on certain benchmarks while reducing feature size by 92%. It is validated against 18 multi-scale benchmarks and compared with various existing algorithms, demonstrating its superiority in performance.

Author

wolfberrypie

Language

EN