Binary Grey Wolf Optimization for Feature Selection

版本 1.3 (62.1 KB) 作者: Jingwei Too
Demonstration on how binary grey wolf optimization (BGWO) applied in the feature selection task.
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更新时间 2020/12/19
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This toolbox offers two types of binary grey wolf optimization (BGWO) methods

The < Main.m file > demos the examples of how BGWO solves the feature selection problem using benchmark data-set.

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Please consider citing my article
[1] Too, Jingwei, et al. “A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification.” Computers, vol. 7, no. 4, MDPI AG, Nov. 2018, p. 58, DOI:https://doi.org/10.3390/computers7040058

[2] Too, Jingwei, and Abdul Rahim Abdullah. “Opposition Based Competitive Grey Wolf Optimizer for EMG Feature Selection.” Evolutionary Intelligence, Springer Science and Business Media LLC, July 2020, DOI: https://doi.org/10.1007/s12065-020-00441-5

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版本 已发布 发行说明
1.3

See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Grey-Wolf-Optimization-for-Feature-Selection/releases/tag/1.3
1.2

Improve code for the fitness function
1.1.0

Change to hold-out
1.0.6

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1.0.5

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1.0.4

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1.0.3

Simplify BGWO1 program.
1.0.2

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1.0.1

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1.0.0

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。