Genetic Programming and Feature Selection for Classification of Breast Masses in Mammograms

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Nandi:2006:EMBS,

• author = "R. J. Nandi and A. K. Nandi and R. Rangayyan and D. Scutt",
• title = "Genetic Programming and Feature Selection for Classification of Breast Masses in Mammograms",
• booktitle = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS '06",
• year = "2006",
• pages = "3021--3024",
• address = "New York, USA",
• month = aug,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "1-4244-003303",
• ISSN = "1557-170X",
• DOI = "doi:10.1109/IEMBS.2006.260460",
• abstract = "A dataset of 57 breast mass mammographic images, each with 22 features computed, was used in this investigation. The extracted features relate to edge-sharpness, shape, and texture. The novelty of this paper is the adaptation and application of genetic programming (GP). To refine the pool of features available to the GP classifier, we used five feature-selection methods, including three statistical measures Student's t-test, Kolmogorov-Smirnov Test, and Kullback-Leibler Divergence. Both the training and test accuracies obtained were above 99.5percent for training and typically above 98percent for testing",
• notes = "Dept. of Electr. Eng. & Electron., Liverpool Univ.",

}

Genetic Programming entries for R J Nandi Asoke K Nandi R M Rangayyan Diane Scutt

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