Investigating the Performance of a Novel Modified Binary Black Hole Optimization Algorithm for Enhancing Feature Selection
Mohammad Ryiad Al-Eiadeh,
Raneem Qaddoura,
Mustafa Abdallah
Abstract:High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At th… Show more
Over the last decade, technological advances have brought breakthroughs in the landscape of data management, transmission, processing, and storage [...]
Over the last decade, technological advances have brought breakthroughs in the landscape of data management, transmission, processing, and storage [...]
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