Performing Feature Selection with ACO

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Abstract

The main aim of feature selection is to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. In real world problems FS is a must due to the abundance of noisy, irrelevant or misleading features. However, current methods are inadequate at finding optimal reductions. This chapter presents a feature selection mechanism based on Ant Colony Optimization in an attempt to combat this. The method is then applied to the problem of finding optimal feature subsets in the fuzzy-rough data reduction process. The present work is applied to two very different challenging tasks, namely web classification and complex systems monitoring.
Original languageEnglish
Title of host publicationSwarm Intelligence and Data Mining
PublisherSpringer Nature
Pages45-73
Number of pages29
Publication statusPublished - 2006

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