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Clustering Algorithms: Experiment and Improvements

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Computing and Network Sustainability

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 12))

Abstract

Clustering is data mining method to divide the data objects into n number of clusters. Clustering algorithms can be used in domains such as e-commerce, bio-informatics, image segmentation, speech recognition, financial analysis, and fraud detection. There is abandon knowledge in the clustering research and applications and also various improvements are done on various clustering algorithms. This paper includes the study and survey of various concepts and clustering algorithms by experimenting on it on some data sets and then analyzed gaps and scope for enhancement and scalability of algorithms. Then improved k-means is proposed to minimize these gaps. This improved algorithm automatically finds value of number of clusters and calculates initial centroids in better way rather random selection. From the experimentation, it is found that numbers of iterations are reduced; clusters quality increased and also minimized empty clusters in proposed algorithm.

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Author information

Authors and Affiliations

  1. Department of CSE, SGB Amravati University, Amravati, India

    Anand Khandare

  2. Department of CSE, PRMIT & R, Badnera, Amravati, India

    A. S. Alvi

Authors
  1. Anand Khandare
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  2. A. S. Alvi
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Corresponding author

Correspondence to Anand Khandare .

Editor information

Editors and Affiliations

  1. Department of Software and Systems Engineering, VIT University, Vellore, Tamil Nadu, India

    H.R . Vishwakarma

  2. Department of Electronics and Communication Engineering, ITM University, Gwalior, Madhya Pradesh, India

    Shyam Akashe

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Khandare, A., Alvi, A.S. (2017). Clustering Algorithms: Experiment and Improvements. In: Vishwakarma, H., Akashe, S. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 12. Springer, Singapore. https://doi.org/10.1007/978-981-10-3935-5_27

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  • DOI: https://doi.org/10.1007/978-981-10-3935-5_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3934-8

  • Online ISBN: 978-981-10-3935-5

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