4.6 Article

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

Journal

NEURAL COMPUTING & APPLICATIONS
Volume 22, Issue 7-8, Pages 1591-1598

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00521-012-0927-0

Keywords

Local linear wavelet neural network (LLWNN); Firefly algorithm (FA); Pattern recognition; Wisconsin breast cancer (WBC); Minimum description length (MDL)

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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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