Year 2018, Volume 1, Issue 1, Pages 24 - 34 2018-12-20

An Optimized RBF-Neural Network for Breast Cancer Classification

Siouda Roguia [1] , Nemissi Mohamed [2]

25 72

This paper introduces an optimized RBF-Neural Network for breast cancer classification. The study is based on the optimization of the network through three learning phases. In the first phase, K-means clustering method is used to define RBFs centers. In the second phase, Particle Swarm Optimization is used to optimize RBFs widths. In this phase, a pseudo inverse solution is used to calculate the output weights. Finally, in the third phase, the back-propagation algorithm is used for fine-tuning the obtained parameters, namely centers, widths and output weights. The back-propagation is then initialized with the obtained parameters instead of a random initialization. To evaluate the performance of the proposed method, tests were performed using the Wisconsin Diagnostic Breast Cancer database. The proposed system was compared with a network trained only with BP and a network trained with K-means + PSO. The results obtained are promising compared to other advanced methods and the proposed learning method gives better results by combining these three methods.


K-means, Radial Basis Function Networks, Classification, Neural Networks, Particle Swarm Optimization
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Primary Language en
Subjects Computer Science, Interdisciplinary Application
Journal Section Articles
Authors

Orcid: 0000-0002-0251-9880
Author: Siouda Roguia (Primary Author)
Institution: 8 Mai 1945 Guelma
Country: Algeria


Author: Nemissi Mohamed
Institution: University of Guelma

Bibtex @research article { ijiam531728, journal = {International Journal of Informatics and Applied Mathematics}, issn = {}, eissn = {2667-6990}, address = {International Society of Academicians}, year = {2018}, volume = {1}, pages = {24 - 34}, doi = {}, title = {An Optimized RBF-Neural Network for Breast Cancer Classification}, key = {cite}, author = {Roguia, Siouda and Mohamed, Nemissi} }
APA Roguia, S , Mohamed, N . (2018). An Optimized RBF-Neural Network for Breast Cancer Classification. International Journal of Informatics and Applied Mathematics, 1 (1), 24-34. Retrieved from http://dergipark.org.tr/ijiam/issue/43831/531728
MLA Roguia, S , Mohamed, N . "An Optimized RBF-Neural Network for Breast Cancer Classification". International Journal of Informatics and Applied Mathematics 1 (2018): 24-34 <http://dergipark.org.tr/ijiam/issue/43831/531728>
Chicago Roguia, S , Mohamed, N . "An Optimized RBF-Neural Network for Breast Cancer Classification". International Journal of Informatics and Applied Mathematics 1 (2018): 24-34
RIS TY - JOUR T1 - An Optimized RBF-Neural Network for Breast Cancer Classification AU - Siouda Roguia , Nemissi Mohamed Y1 - 2018 PY - 2018 N1 - DO - T2 - International Journal of Informatics and Applied Mathematics JF - Journal JO - JOR SP - 24 EP - 34 VL - 1 IS - 1 SN - -2667-6990 M3 - UR - Y2 - 2019 ER -
EndNote %0 International Journal of Informatics and Applied Mathematics An Optimized RBF-Neural Network for Breast Cancer Classification %A Siouda Roguia , Nemissi Mohamed %T An Optimized RBF-Neural Network for Breast Cancer Classification %D 2018 %J International Journal of Informatics and Applied Mathematics %P -2667-6990 %V 1 %N 1 %R %U
ISNAD Roguia, Siouda , Mohamed, Nemissi . "An Optimized RBF-Neural Network for Breast Cancer Classification". International Journal of Informatics and Applied Mathematics 1 / 1 (December 2018): 24-34.