1. Title: Breast Cancer Dataset

2. Relevant Information Paragraph:

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/

3. Number of Instances: 569

4. Number of Attributes: 30

5. Missing Attribute Values: none

6. Class distribution (number of instances per class)

    class            N              N[%]
  -----------------------------------
   benign      357          62.742
malignant    212          37.258