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A Hybrid Model of Clustering and Classification to Enhance the Performance of a Classifier

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Book cover Advanced Informatics for Computing Research (ICAICR 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1076))

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Abstract

Clustering and Classification are significant and widely used task in data mining. Their incorporation together is rare. When we integrate them together they can give more promising, accurate and robust results compare to - unaccompanied. The integration of these methods can be done by an ensemble method or hybrid method. This paper uses a hybrid model; K-means clustering method for the preprocessing of the data. Pre-learning by K-means clustering keeps similar cases in the same group. This improves the on-hand classifier’s performance. To demonstrate applicability of this new hybrid approach the experiments on PIMA diabetic datasets from UCI repository were conducted and the results are compared on several parameters. Clustering before classification provides an added description to the data and improves the effectiveness of the classification task. This model can be deployed with any classification algorithms to improve its performance.

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Author information

Authors and Affiliations

  1. Computer Science Department, NRI Group of Institutes, Bhopal, M.P., India

    Subodhini Gupta

  2. Department of Computer Science and Engineering, Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India

    Bhushan Parekh & Anjali Jivani

Authors
  1. Subodhini Gupta
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  2. Bhushan Parekh
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  3. Anjali Jivani
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Corresponding author

Correspondence to Subodhini Gupta .

Editor information

Editors and Affiliations

  1. Papua New Guinea University of Technology, Lae, Papua New Guinea

    Ashish Kumar Luhach

  2. Computer Science Department, Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

  3. Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Kamarul Bin Ghazali Hawari

  4. School of Computing, University of Eastern Finland, Kuopio, Finland

    Xiao-Zhi Gao

  5. Department of Mathematics and Computing Science, Saint Mary's University, Halifax, Canada

    Pawan Lingras

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Gupta, S., Parekh, B., Jivani, A. (2019). A Hybrid Model of Clustering and Classification to Enhance the Performance of a Classifier. In: Luhach, A., Jat, D., Hawari, K., Gao, XZ., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2019. Communications in Computer and Information Science, vol 1076. Springer, Singapore. https://doi.org/10.1007/978-981-15-0111-1_34

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  • DOI: https://doi.org/10.1007/978-981-15-0111-1_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0110-4

  • Online ISBN: 978-981-15-0111-1

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