KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on)

KEEL-dataset - data set description

Mammographic Mass data set

Description
Files and additional references

Description

This section describes main characteristics of the mammographic data set and its attributes:

General information

Mammographic Mass data set
Type	Classification	Origin	Real world
Features	5	(Real / Integer / Nominal)	(0 / 5 / 0)
Classes	2	Missing values?	Yes
Total instances	961	Instances without missing values	830

Attribute description

Attribute	Domain
BI-RADS	[0,6]
Age	[18,96]
Shape	[1,4]
Margin	[1,5]
Density	[1,4]
Severity	{0, 1}

Additional information

This data set can be used to predict the severity (benign or malignant) of a mammographic mass lesion from BI-RADS attributes and the patient's age.

It contains a BI-RADS assessment, the patient's age and three BI-RADS attributes together with the ground truth (the severity field, which is the target attribute).

The data was collected at the Institute of Radiology of the University Erlangen-Nuremberg between 2003 and 2006.

Files and additional references

In this section you can download some files related to the mammographic data set:

The complete data set already formatted in KEEL formatcan be downloaded from here .
A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here .
A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here .
The header file associated to this data set can be downloaded from here .
This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass.