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Differential Evolution (DE) Clustering

version 1.0.1 (840 KB) by Seyed Muhammad Hossein Mousavi
Differential Evolution Clustering and comparison with k-means and Gaussian Mixture Model


Updated 08 Jan 2022

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%% Differential Evolution Clustering - (7 Jan 2022) % Here, we are using evolutionary algorithms, in order to perform % clustering task. The selected algorithm is Differential Evolution (DE) % evolutionary computation as it is faster than others. We are using HTRU2 % dataset which is consisted of 17898 samples and 9 features. Features 5 to % 8 are used in this code. All 4 selected features combinations are % clustered and compared with K-Means clustering and Gaussian Mixture Model % (GMM) Clustering visually and statistically. You can use your data and define % your parameters. 'K' is the number of clusters, 'MaxIt' is number of % iterations and 'nPop' is population size which are most important % parameters. % ------------------------------------------------ % System is using the following paper as dataset: % R. J. Lyon, B. W. Stappers, S. Cooper, J. M. Brooke, J. D. Knowles, Fifty Years of Pulsar Candidate Selection: From simple filters to a new principled real-time classification approach, Monthly Notices of the Royal Astronomical Society 459 (1), 1104-1123, DOI: 10.1093/mnras/stw656 % This code is part of following projects, so please cite them to: % Mousavi, Seyed Muhammad Hossein, S. Younes MiriNezhad, and Atiye Mirmoini. "A new support vector finder method, based on triangular calculations and K-means clustering." 2017 9th International Conference on Information and Knowledge Technology (IKT). IEEE, 2017. % Mousavi, Seyed Muhammad Hossein, Vincent Charles, and Tatiana Gherman. "An Evolutionary Pentagon Support Vector Finder Method." Expert Systems with Applications 150 (2020): 113284. % ------------------------------------------------ % Feel free to ontact me if you find any problem using the code: % % SeyedMuhammadHosseinMousavi % My Google Scholar: % My GitHub: % My ORCID: % My Scopus: % My MathWorks: % ------------------------------------------------ % Enjoy the code and wish me luck :)

Cite As

Seyed Muhammad Hossein Mousavi (2022). Differential Evolution (DE) Clustering (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019a
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