Binary Tree Growth Algorithm for Feature Selection

A feature selection algorithm, named as Binary Tree Growth Algorithm (BTGA) is applied for feature selection tasks.

https://github.com/JingweiToo/Binary-Tree-Growth-Algorithm-for-Feature-Selection

Version 1.3 (61.5 KB)
298 Downloads
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20 Dec 2020

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This toolbox offers a Binary Tree Growth Algorithm (BTGA)

The < Main.m file > illustrates the example of how BTGA can solve the feature selection problem using benchmark data-set.

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Cite As

Too, Jingwei, et al. “Feature Selection Based on Binary Tree Growth Algorithm for the Classification of Myoelectric Signals.” Machines, vol. 6, no. 4, MDPI AG, Dec. 2018, p. 65, doi:10.3390/machines6040065.

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General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
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Version Published Release Notes
1.3

See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Tree-Growth-Algorithm-for-Feature-Selection/releases/tag/1.3
1.2

Improve code for the fitness function
1.1.0

change to hold-out
1.0.4

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1.0.3

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1.0.2

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1.0.1

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1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.