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A Teaching–Learning-Based Particle Swarm Optimization for Data Clustering

  • Neetu Kushwaha
  • Millie Pant
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 748)

Abstract

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.

Keywords

Teaching–learning-based optimization K-means Clustering Particle swarm optimization 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Applied Science and EngineeringIndian Institute of Technology RoorkeeRoorkeeIndia

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