%BREAST 699 objects with 9 features in 2 classes % % X = BREAST % % Breast cancer Wisconsin dataset obtained from the University of Wisconsin % Hospitals, Madison from Dr. William H. Wolberg. % % REFERENCE % O. L. Mangasarian and W. H. Wolberg: "Cancer diagnosis via linear % programming", SIAM News, Volume 23, Number 5, September 1990, pp 1 & 18. % % X = BREAST(VAL) % % By default objects with missing values are removed. When something else % is desired, use one of the options in MISVAL for VAL. % % SEE ALSO PRTools Guide, UCI Website % PRTOOLS, DATASETS, MISVAL % Copyright: R.P.W. Duin function a = breast(val) if nargin < 1, val = 'remove'; end a = pr_loadmatfile; if isempty(a) opt.delimeter = ','; opt.labfeat = 11; opt.featnames = {'Clump Thickness' 'Uniformity of Cell Size' ... 'Uniformity of Cell Shape' 'Marginal Adhesion' ... 'Single Epithelial Cell Size' 'Bare Nuclei' 'Bland Chromatin' ... 'Normal Nucleoli' 'Mitoses'}; opt.feats = [2:10]; opt.misvalue = -1; opt.classnames = {'benign' 'malignant'}; opt.desc='The original database of the Wisconsin Breast Cancer Databases from UCI, containing 699 instances, collected between 1989 and 1991. '; opt.link = 'ftp://ftp.ics.uci.edu/pub/machine-learning-databases/breast-cancer-wisconsin/'; opt.dsetname = 'Breast Wisconsin'; a = pr_download('http://prtools.tudelft.nl/prdatasets/breastorg.dat',[],opt); end a = misval(a,val); return