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Data Clustering Using Harmony Search Algorithm

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7077))

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Abstract

Being one of the main challenges to clustering algorithms, the sensitivity of fuzzy c-means (FCM) and hard c-means (HCM) to tune the initial clusters centers has captured the attention of the clustering communities for quite a long time. In this study, the new evolutionary algorithm, Harmony Search (HS), is proposed as a new method aimed at addressing this problem. The proposed approach consists of two stages. In the first stage, the HS explores the search space of the given dataset to find out the near-optimal cluster centers. The cluster centers found by the HS are then evaluated using reformulated c-means objective function. In the second stage, the best cluster centers found are used as the initial cluster centers for the c-means algorithms. Our experiments show that an HS can minimize the difficulty of choosing an initialization for the c-means clustering algorithms. For purposes of evaluation, standard benchmark data are experimented with, including the Iris, BUPA liver disorders, Glass, Diabetes, etc. along with two generated data that have several local extrema.

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Author information

Authors and Affiliations

  1. Faculty of Computing and Information Technology, University of Tabuk, Tabuk, Kingdom of Saudi Arabia

    Osama Moh’d Alia

  2. School of Computer Sciences, Universiti Sains Malaysia, 11800, Penang, Malaysia

    Mohammed Azmi Al-Betar, Rajeswari Mandava & Ahamad Tajudin Khader

  3. School of Computer Science, AL-Zaytoonah University of Jordan, Amman, Jordan, Malaysia

    Mohammed Azmi Al-Betar

Authors
  1. Osama Moh’d Alia
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  2. Mohammed Azmi Al-Betar
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  3. Rajeswari Mandava
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  4. Ahamad Tajudin Khader
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT, Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Department of Electronics and Telecommunications, Jadavpur University, 700032, Kolkata, India

    Swagatam Das

  4. ANITS, Visakhapatnam, India

    Suresh Chandra Satapathy

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© 2011 Springer-Verlag Berlin Heidelberg

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Alia, O.M., Al-Betar, M.A., Mandava, R., Khader, A.T. (2011). Data Clustering Using Harmony Search Algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-27242-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27241-7

  • Online ISBN: 978-3-642-27242-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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