Discrimination methods for the classification of breast cancer diagnosis

Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

Volumn 1, Issue , 2005, Pages 259-261

  Si, Shou Kui ^a   Wang, Xiao Feng ^a   Sun, Xi Jing ^a  

^a NAVAL AERONAUTICAL AND ASTRONAUTICAL UNIVERSITY   (China)

Author keywords

Classification; Discrimination method; Fisher discrimination; Mahalanobis distances; Support vector machine

Indexed keywords

COMPUTER AIDED DIAGNOSIS; LEARNING SYSTEMS; PATTERN RECOGNITION;

DISCRIMINATION METHOD; FISHER DISCRIMINATION; MAHALANOBIS DISTANCES; SUPPORT VECTOR MACHINE (SVM);

TUMORS;

EID: 33847119453     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Sandrine Dudoit, Jane Fridlyand, and Terence P. Speed, "Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data, " Journal of the American Statistical Association, pp. 77-87, Mar. 2002.
2. Yuh-Jye Lee and O. L., "SSVM: A Smooth Support Vector Machine for Classification," Computational Optimization and Applications, Vol. 20, No. 1, pp. 5-22, 2000.
3. Olvi L. Mangasarian, W. Nick Street, and William H. Wolberg, "Breast cancer diagnosis and prognosis via linear programming," Technical Report MP-TR-1994-10, MP-TR, 1994.
4. K. Fukumizu, Statistical Pattern Recognition, Acad. Press, NY, 1989.
5. L. Kaufman, "Solving the quadratic programming problem arising in support vector classification," In Bernhard Schölkopf, Chistopher J. C. Burges, and Alexander J. Smola, editors, Advances in Kernel Methods, Support Vector Learning, pp. 147-167, MIT Press, 1999.