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9. Binary Bat Algorithm for Feature Selection
出版Elsevier Inc. Chapters, 2013-05-16
主題Computers / GeneralTechnology & Engineering / Electronics / DigitalMathematics / AppliedComputers / BioinformaticsComputers / Mathematical & Statistical SoftwareTechnology & Engineering / Engineering (General)Technology & Engineering / Electronics / General
ISBN01280689579780128068953
URLhttp://books.google.com.hk/books?id=s4hzDAAAQBAJ&hl=&source=gbs_api
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註釋Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques.