Breast Cancer Wisconsin (Diagnostic)

Donated on 11/1/1995

Diagnostic Wisconsin Breast Cancer Database.

Dataset Characteristics

Multivariate

Subject Area

Life

Associated Tasks

Classification

Attribute Type

Real

# Instances

569

# Attributes

30

Information

Additional Information

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 http://www.cs.wisc.edu/~street/images/ 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. 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]. This database is also available through the UW CS ftp server: ftp ftp.cs.wisc.edu cd math-prog/cpo-dataset/machine-learn/WDBC/

Has Missing Values

Symbol: 0

Features

Attribute NameRoleTypeDescriptionUnitsMissing Values
IDIDCategoricalfalse
DiagnosisTargetCategoricalfalse
radius1FeatureContinuousfalse
texture1FeatureContinuousfalse
perimeter1FeatureContinuousfalse
area1FeatureContinuousfalse
smoothness1FeatureContinuousfalse
compactness1FeatureContinuousfalse
concavity1FeatureContinuousfalse
concave_points1FeatureContinuousfalse

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Baseline Model Performance

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Keywords

healthcancer

Creators

William Wolberg

Olvi Mangasarian

Nick Street

License

This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

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