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

Appendicitis data set

Description
Files and additional references

Description

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

General information

Appendicitis data set
Type	Classification	Origin	Real world
Features	7	(Real / Integer / Nominal)	(7 / 0 / 0)
Instances	106	Classes	2
Missing values?			No

Attribute description

Attribute	Domain
At1	[0.0,1.0]
At2	[0.0,1.0]
At3	[0.0,1.0]
At4	[0.0,1.0]
At5	[0.0,1.0]
At6	[0.0,1.0]
At7	[0.0,1.0]
Class	{0,1}

Additional information

This dataset was proposed in S. M. Weiss, and C. A. Kulikowski, Computer Systems That Learn (1991).

The data represents 7 medical measures taken over 106 patients on which the class label represents if the patient has appendicitis (class label 1) or not (class label 0).

Files and additional references

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

The complete data set already formatted in KEEL format can 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 .