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PSO Feature Selection and optimization

version 1.1.0.0 (7.23 KB) by Abbas Manthiri S
This code use as optimization of data by row or coulmn

2.9K Downloads

Updated 24 Mar 2017

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In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity. Each particle's movement is influenced by its local best known position, but is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.

Cite As

Abbas Manthiri S (2022). PSO Feature Selection and optimization (https://www.mathworks.com/matlabcentral/fileexchange/62214-pso-feature-selection-and-optimization), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Acknowledgements

Inspired: 13 Datasets for Feature Selection

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