Binary Tree Growth Algorithm for Feature Selection

Version 1.3 (61.5 KB) by Jingwei Too
A feature selection algorithm, named as Binary Tree Growth Algorithm (BTGA) is applied for feature selection tasks.
281 Downloads
Updated 20 Dec 2020

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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MATLAB Release Compatibility
Created with R2018a
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

-

1.0.3

-

1.0.2

-

1.0.1

-

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.