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Local linear wavelet neural network based breast tumor classification using firefly algorithm

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Abstract

Breast cancer is the major cause of cancer deaths in women today and it is the most common type of cancer in women. This paper presents some experiments for classifying breast cancer tumor and proposes the use of firefly algorithm (FA) to improve the performance of Local linear wavelet neural network. This work in fact uses FA to optimize the parameters of local linear wavelet neural network. The experiments were conducted on extracted breast cancer data from University of Winconsin Hospital, Madison. The result has been compared with a wide range of classifiers to evaluate its performance. The evaluations show that the proposed approach is very robust, effective and gives better correct classification as compared to other classifiers.

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Notes

  1. http://ailab.si/orange/doc/datasets/breast-cancer-wisconsin-cont.html.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Krupajal Engineering College, Biju Patnaik University of Technology, Rourkela, 752002, India

    M. R. Senapati

  2. S ‘O’ A University, Bhubaneswar, 752020, India

    P. K. Dash

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  1. M. R. Senapati
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  2. P. K. Dash
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Correspondence to M. R. Senapati.

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Senapati, M.R., Dash, P.K. Local linear wavelet neural network based breast tumor classification using firefly algorithm. Neural Comput & Applic 22, 1591–1598 (2013). https://doi.org/10.1007/s00521-012-0927-0

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  • DOI: https://doi.org/10.1007/s00521-012-0927-0

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