The present study proposes TLBO-PSO an integrated Teacher–Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) for optimum data clustering. TLBO-PSO algorithm searches through arbitrary datasets for appropriate cluster centroid and tries to find the global optima efficiently. The proposed TLBO-PSO is analyzed on a set of six benchmark datasets available at UCI machine learning repository. Experimental result shows that the proposed algorithm performs better than the other state-of-the-art clustering algorithms.
CITATION STYLE
Kushwaha, N., & Pant, M. (2019). A teaching–Learning-based particle swarm optimization for data clustering. In Advances in Intelligent Systems and Computing (Vol. 748, pp. 223–233). Springer Verlag. https://doi.org/10.1007/978-981-13-0923-6_19
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