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Finding Clusters of Data: Cluster Analysis in R

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Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 515))

Abstract

The paper discusses an essential data mining task, clustering. Clustering groups similar instances and results in classes of similar instances. In this paper, clustering methods k-means, SOM clustering, and hierarchical method of clustering are discussed and implemented in R. Before the application of clustering algorithms cluster tendency is evaluated to determine whether the data set is appropriate for clustering or not. Cluster tendency is also discussed in the paper.

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Author information

Authors and Affiliations

  1. University of Allahabad, Allahabad, India

    Tulika Narang

Authors
  1. Tulika Narang
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Corresponding author

Correspondence to Tulika Narang .

Editor information

Editors and Affiliations

  1. ANITS, Prof., Comp. Sci. & Engg. Dept. ANITS, Visakhapatnam, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Dept. of ECE, Shri Ramswaroop Mem. Group of Prof. Clg Dept. of ECE, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. SCIS, University of Hyderabad , Hyderabad, India

    Siba K. Udgata

  4. KIIT University, School of Computer Engineering KIIT University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

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Narang, T. (2017). Finding Clusters of Data: Cluster Analysis in R. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_63

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  • DOI: https://doi.org/10.1007/978-981-10-3153-3_63

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3152-6

  • Online ISBN: 978-981-10-3153-3

  • eBook Packages: EngineeringEngineering (R0)

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