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Bat algorithm-based weighted Laplacian probabilistic neural network

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Abstract

Probabilistic neural network (PNN) is a single-pass feed-forward neural network with the capability of providing nonlinear decision boundaries. In this work, we propose the modifications to the existing PNN approach. Contributions are threefold: First, symmetric Laplace distribution has been used instead of Gaussian distribution in the pattern layer of the PNN approach. Second, a new weight coefficients’ estimation method has been introduced between the pattern and summation layers of PNN. Third, a novel convex fitness function has been designed for the bat algorithm to obtain an optimal smoothing parameter vector. The designed fitness function maintains a balance between the sensitivity and specificity values. The performance of the proposed algorithm “bat algorithm-based weighted Laplacian probabilistic neural network” is compared with that of conventional PNN, weighted PNN, extreme learning method, optimal pruned extreme learning machine and K-nearest neighbor. Experimental evaluation is carried out on eleven benchmark data sets using different performance measures such as accuracy, sensitivity, specificity and Youden’s index. The comparative performance evaluation of the proposed model has been made with the PNN, and other standard algorithms outperform the compared approaches in terms of classification accuracy. Friedman test is used for statistical evaluation of the proposed approach.

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Acknowledgements

The authors are thankful to Prof. Gopal Mugeraya, Director of National Institute of Technology Goa, for providing required help and support. Also we would like to thank DST SERB for providing computational facilities [File Number: YSS/2015/001636].

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Goa, Farmagudi, Goa, India

    Shraddha M. Naik & Venkatnareshbabu Kuppili

  2. Department of Applied Sciences, National Institute of Technology Goa, Farmagudi, Goa, India

    Ravi Prasad K. Jagannath

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  1. Shraddha M. Naik
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  2. Ravi Prasad K. Jagannath
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  3. Venkatnareshbabu Kuppili
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Correspondence to Shraddha M. Naik.

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Naik, S.M., Jagannath, R.P.K. & Kuppili, V. Bat algorithm-based weighted Laplacian probabilistic neural network. Neural Comput & Applic 32, 1157–1171 (2020). https://doi.org/10.1007/s00521-019-04475-4

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