SVM approach to breast cancer classification

Proceedings - 2nd International Multi-Symposiums on Computer and Computational Sciences, IMSCCS'07

Volumn , Issue , 2007, Pages 32-37

  Sewak, Mihir ^a   Vaidya, Priyanka ^a   Chan, Chien Chung ^a   Duan, Zhong Hui ^a,b  

^a University of Akron

^b UNIVERSITY OF AKRON   (United States)

Author keywords

Breast cancer; Classifiers; Ensemble; Machine learning; Support vector machines

Indexed keywords

(E ,3E) PROCESS; BENIGN TUMOR; BREAST CANCERS; CLASSIFICATIO N PROBLEMS; COMPUTATIONAL SCIENCES; DATA SETS; FINE NEEDLE ASPIRATION (FNA); GAUSSIAN RADIAL BASIS FUNCTION (RBF) KERNEL; INTERNATIONAL (CO); PREDICTION ACCURACY; SUPPORT VECTORS; TESTING DATA; TRAINING SETS; UNIVERSITY OF WISCONSIN (UW); VECTOR MACHINES; WISCONSIN (USA);

CLASSIFICATION (OF INFORMATION); HEALTH; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 46449111166     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IMSCCS.2007.4392577     Document Type: Conference Paper

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