Friday 29th of March 2024
 

Cooperative Swarm based Evolutionary Approach to findoptimal cluster centroids in Cluster Analysis


Bighnaraj Naik, Sarita Mahapatra, Subhra Swetanisha and Swadhin Kumar Barisal

Centroid-based clustering is a NP-hard optimization problem, and thus the common approach is to search for cluster centers only for approximate solutions. Well-known centroid-based clustering methods are k-means, k-medoids and fuzzy c-means. In this paper we proposed swarm intelligence based natureinspired center-based clustering method using PSO optimization. PSO searches the optimized solution from available solutions in multidimensional search space. So PSO is capable to search best cluster with maximum fitness using social-only model and cognition-only model, such that the square distances from the cluster are minimized. In this article, it is shown that how PSO based clustering can be used to find N number of cluster specified by the user in a dataset. Our suggested method has been tested with artificial dataset and several real multidimensional dataset from UCI repository. Effectiveness of the method is demonstrated by comparing fitness of proposed method with effectiveness of K-means and Fuzzy c-means technique. Results shows that, this method is quite simple, effective and has much potential to search best cluster centers in multidimensional search space.

Keywords: Centroid-based clustering; Cluster Analysis; Swarm

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ABOUT THE AUTHORS

Bighnaraj Naik
He has received B.E degree in Information Technology from National Institute of Science and Technology, India, and the MTech degree in computer science from the Institute of Technical Education and Research, Siksha ‘O’ Anushandhan University, India. He is currently working as an Assistant Professor in the department of Information Technology at Institute of Technical Education and Research, Siksha ‘O’ Anushandhan University, India. His main research interests are in the areas of design and analysis of algorithm, data mining, pattern recognition and natured inspired computing. He is a member of IAENG Society (Member Number: 115149).

Sarita Mahapatra
She received the B.Tech degree in information technology from the Synergy Institute of Technology, under Uttkal University and M.Tech from Institute of Technical Education and Research, Siksha ‘O’ Anushandhan University, india. She is a lecturer in the Department of Information Technology, ITER, Siksha ‘O’ Anushandhan University, where she is teaching since last 5 year. Her research interests are in the areas of data mining and pattern recognition.

Subhra Swetanisha
She has been an Assistant Professor with the department of Computer Science and Engineering in Trident Academy of Technology Bhubaneswar, Odisha, India.She has received MTech degree in Computer Science and Engineering from KIIT University, India. Her current research interest includes Genetic-Fuzzy-Neural systems, Data Mining, and Image Processing.She is a member of Indian Society for Technical Education(ISTE) with member id LM78439.

Swadhin Kumar Barisal
He has received M.TECH. degree in Computer science and engineering from Indian Institute of Technology , Kharagpur, India, and the BTech degree in computer science from Synergy Institute of Engineering and Technology, Odisha,India. He is currently working as an Assistant Professor in the department of Computer science and engineering at Institute of Technical Education and Research, Siksha ‘O’ Anushandhan University, India. His main research interests are in the areas of design and analysis of algorithm, data mining, and pattern recognition and also object oriented technology. He is a member of IAENG Society (Member Number: 119595).


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