Training of Multilayer Perceptron Neural Networks by Using Cellular Genetic Algorithms

This paper deals with a method for training neural networks by using cellular genetic algorithms (CGA). This method was implemented as software, CGANN-Trainer, which was used to generate binary classifiers for recognition of patterns associated with breast cancer images in a multi-objective optimization problem. The results reached by the CGA with the Wisconsin Breast Cancer Database, and the Wisconsin Diagnostic Breast Cancer Database, were compared with some other methods previously reported using the same databases, proving to be an interesting alternative.

[1]  O. Mangasarian,et al.  Pattern Recognition Via Linear Programming: Theory and Application to Medical Diagnosis , 1989 .

[2]  Takis Kasparis,et al.  Coupling weight elimination and genetic algorithms , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[3]  Sam Kwong,et al.  Hierarchical Genetic Algorithm , 1999 .

[4]  Filippo Menczer,et al.  Local Selection , 1998, Evolutionary Programming.

[5]  Kuhu Pal,et al.  Breast cancer detection using rank nearest neighbor classification rules , 2003, Pattern Recognit..

[6]  Sam Kwong,et al.  Genetic Algorithms : Concepts and Designs , 1998 .

[7]  A. E. Eiben,et al.  Evolutionary Programming VII , 1998, Lecture Notes in Computer Science.

[8]  Moshe Sipper,et al.  A fuzzy-genetic approach to breast cancer diagnosis , 1999, Artif. Intell. Medicine.

[9]  L. Darrell Whitley,et al.  An overview of evolutionary algorithms: practical issues and common pitfalls , 2001, Inf. Softw. Technol..

[10]  Martin T. Hagan,et al.  Neural network design , 1995 .

[11]  William Nick Street,et al.  Cancer diagnosis and prognosis via linear-programming-based machine learning , 1994 .

[12]  Olu Lafe,et al.  Cellular Automata Transforms , 2000, Multimedia Systems and Applications Series.

[13]  Rudy Setiono,et al.  Extracting rules from pruned networks for breast cancer diagnosis , 1996, Artif. Intell. Medicine.

[14]  O. Mangasarian,et al.  Multisurface method of pattern separation for medical diagnosis applied to breast cytology. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Jianping Zhang,et al.  Selecting Typical Instances in Instance-Based Learning , 1992, ML.

[16]  Alan F. Murray,et al.  IEEE International Conference on Neural Networks , 1997 .

[17]  Joydeep Ghosh,et al.  Evaluation and ordering of rules extracted from feedforward networks , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

[18]  Huan Liu,et al.  Symbolic Representation of Neural Networks , 1996, Computer.