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

Heart Disease (Cleveland) data set

Description
Files and additional references

Description

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

General information

Heart Disease (Cleveland) data set
Type	Classification	Origin	Real world
Features	13	(Real / Integer / Nominal)	(13 / 0 / 0)
Classes	5	Missing values?	Yes
Total instances	303	Instances without missing values	297

Attribute description

Attribute	Domain	Attribute	Domain
Age	[29.0, 77.0]	Thalach	[71.0, 202.0]
Sex	[0.0, 1.0]	Exang	[0.0, 1.0]
Cp	[1.0, 4.0]	Oldpeak	[0.0, 6.2]
Trestbps	[94.0, 200.0]	Slope	[1.0, 3.0]
Chol	[126.0, 564.0]	Ca	[0.0, 3.0]
Fbs	[0.0, 1.0]	Thal	[3.0, 7.0]
Restecg	[0.0, 2.0]	Num	{0,1,2,3,4}

Additional information

This data set is a part of the Heart Disease Data Set (the part obtained from the V.A. Medical Center, Long Beach and Cleveland Clinic Foundation), using a subset of 14 attributes. The task is to detect the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4.

Files and additional references

In this section you can download some files related to the cleveland 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/Heart+Disease.