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A Harmony Search Based Gradient Descent Learning-FLANN (HS-GDL-FLANN) for Classification

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Book cover Computational Intelligence in Data Mining - Volume 2

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 32))

Abstract

The Harmony Search (HS) algorithm is meta-heuristic optimization inspired by natural phenomena called musical process and it quite simple due to few mathematical requirements and simple steps as compared to earlier meta-heuristic optimization algorithms. It mimics the local and global search procedure of pitch adjustment during production of pleasant harmony by musicians. Although HS has been used in many application like vehicle routing problems, robotics, power and energy etc., in this paper, an attempt is made to design a hybrid FLANN with Harmony Search based Gradient Descent Learning for classification. The proposed algorithm has been compared with FLANN, GA based FLANN and PSO based FLANN classifier to get remarkable performance. All the four classifier are implemented in MATLAB and tested by couples of benchmark datasets from UCI machine learning repository. Finally, to get generalized performance, 5 fold cross validation is adopted and result are analyzed under one-way ANOVA test.

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Author information

Authors and Affiliations

  1. Department of Computer Science Engineering and Information Technology, Veer Surendra Sai University of Technology, Burla, Sambalpur, 768018, Odisha, India

    Bighnaraj Naik, Janmenjoy Nayak & H. S. Behera

  2. Machine Intelligence Research Labs (MIR Labs), Washington, USA

    Ajith Abraham

  3. IT4Innovations—Center of Excellence, VSB—Technical University of Ostrava, Ostrava, Czech Republic

    Ajith Abraham

Authors
  1. Bighnaraj Naik
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  2. Janmenjoy Nayak
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  3. H. S. Behera
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  4. Ajith Abraham
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Corresponding author

Correspondence to Bighnaraj Naik .

Editor information

Editors and Affiliations

  1. University of Canberra, Canberra, Australia and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Naik, B., Nayak, J., Behera, H.S., Abraham, A. (2015). A Harmony Search Based Gradient Descent Learning-FLANN (HS-GDL-FLANN) for Classification. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 2. Smart Innovation, Systems and Technologies, vol 32. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2208-8_48

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  • DOI: https://doi.org/10.1007/978-81-322-2208-8_48

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