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--- |
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task_categories: |
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- tabular-classification |
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tags: |
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- tabular |
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- breast-cancer |
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pretty_name: WisconsinBreastCancerDiagnostic |
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size_categories: |
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- n<1K |
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--- |
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## Source: |
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Copied from the [original dataset](https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic)) |
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### Creators: |
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1. Dr. William H. Wolberg, General Surgery Dept. |
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University of Wisconsin, Clinical Sciences Center |
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Madison, WI 53792 |
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wolberg '@' eagle.surgery.wisc.edu |
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2. W. Nick Street, Computer Sciences Dept. |
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University of Wisconsin, 1210 West Dayton St., Madison, WI 53706 |
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street '@' cs.wisc.edu 608-262-6619 |
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3. Olvi L. Mangasarian, Computer Sciences Dept. |
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University of Wisconsin, 1210 West Dayton St., Madison, WI 53706 |
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olvi '@' cs.wisc.edu |
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### Donor: |
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Nick Street |
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## Data Set Information: |
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Features 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] |
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Separating 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. |
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The 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]. |
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This database is also available through the UW CS ftp server: |
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ftp ftp.cs.wisc.edu |
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cd math-prog/cpo-dataset/machine-learn/WDBC/ |
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### Attribute Information: |
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1) ID number |
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2) Diagnosis (M = malignant, B = benign) |
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3-32) |
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Ten real-valued features are computed for each cell nucleus: |
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a) radius (mean of distances from center to points on the perimeter) |
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b) texture (standard deviation of gray-scale values) |
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c) perimeter |
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d) area |
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e) smoothness (local variation in radius lengths) |
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f) compactness (perimeter^2 / area - 1.0) |
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g) concavity (severity of concave portions of the contour) |
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h) concave points (number of concave portions of the contour) |
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i) symmetry |
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j) fractal dimension ("coastline approximation" - 1) |
