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    "description": "**Author**: William H. Wolberg, W. Nick Street, Olvi L. Mangasarian    \n**Source**: UCI   \n**Please cite**:   \n\n* Title: \n\nBreast Cancer Wisconsin (Diagnostic) Data Set (WDBC)\n\n* Abstract: \n\nDiagnostic Wisconsin Breast Cancer Database\n\n* Source:\n\nCreators: \n\n1. Dr. William H. Wolberg, General Surgery Dept. \nUniversity of Wisconsin, Clinical Sciences Center \nMadison, WI 53792 \nwolberg '@' eagle.surgery.wisc.edu \n\n2. W. Nick Street, Computer Sciences Dept. \nUniversity of Wisconsin, 1210 West Dayton St., Madison, WI 53706 \nstreet '@' cs.wisc.edu 608-262-6619 \n\n3. Olvi L. Mangasarian, Computer Sciences Dept. \nUniversity of Wisconsin, 1210 West Dayton St., Madison, WI 53706 \nolvi '@' cs.wisc.edu \n\nDonor: Nick Street\n\n* Data Set Information:\n\nFeatures are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. A few of the images can be found at [Web Link] \n\nSeparating plane described above was obtained using Multisurface Method-Tree (MSM-T) [K. P. Bennett, \"Decision Tree Construction Via Linear Programming.\" Proceedings of the 4th Midwest Artificial Intelligence and Cognitive Science Society, pp. 97-101, 1992], a classification method which uses linear programming to construct a decision tree. Relevant features were selected using an exhaustive search in the space of 1-4 features and 1-3 separating planes. \n\nThe actual linear program used to obtain the separating plane in the 3-dimensional space is that described in: [K. P. Bennett and O. L. Mangasarian: \"Robust Linear Programming Discrimination of Two Linearly Inseparable Sets\", Optimization Methods and Software 1, 1992, 23-34]. \n\nThis database is also available through the UW CS ftp server: \nftp ftp.cs.wisc.edu \ncd math-prog\/cpo-dataset\/machine-learn\/WDBC\/\n\n\n* Attribute Information:\n\n1) ID number \n2) Diagnosis (M = malignant, B = benign) \n3-32) \n\nTen real-valued features are computed for each cell nucleus: \n\na) radius (mean of distances from center to points on the perimeter) \nb) texture (standard deviation of gray-scale values) \nc) perimeter \nd) area \ne) smoothness (local variation in radius lengths) \nf) compactness (perimeter^2 \/ area - 1.0) \ng) concavity (severity of concave portions of the contour) \nh) concave points (number of concave portions of the contour) \ni) symmetry \nj) fractal dimension (\"coastline approximation\" - 1)\n\n\n* Relevant Papers:\n\nW.N. Street, W.H. Wolberg and O.L. Mangasarian. Nuclear feature extraction for breast tumor diagnosis. IS&T\/SPIE 1993 International Symposium on Electronic Imaging: Science and Technology, volume 1905, pages 861-870, San Jose, CA, 1993. \n[Web Link] \n\nO.L. Mangasarian, W.N. Street and W.H. Wolberg. Breast cancer diagnosis and prognosis via linear programming. Operations Research, 43(4), pages 570-577, July-August 1995. \n[Web Link] \n\nW.H. Wolberg, W.N. Street, and O.L. Mangasarian. Machine learning techniques to diagnose breast cancer from fine-needle aspirates. Cancer Letters 77 (1994) 163-171. \n\nW.H. Wolberg, W.N. Street, and O.L. Mangasarian. Image analysis and machine learning applied to breast cancer diagnosis and prognosis. Analytical and Quantitative Cytology and Histology, Vol. 17 No. 2, pages 77-87, April 1995. \n\nW.H. Wolberg, W.N. Street, D.M. Heisey, and O.L. Mangasarian. Computerized breast cancer diagnosis and prognosis from fine needle aspirates. Archives of Surgery 1995;130:511-516. \n\nW.H. Wolberg, W.N. Street, D.M. Heisey, and O.L. Mangasarian. Computer-derived nuclear features distinguish malignant from benign breast cytology. Human Pathology, 26:792--796, 1995. \n\n",
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