rtkpp (version 0.8.5)

HeartDisease.cat: Mixed data : Cleveland Heart Disease Data

Description

The Cleveland Heart Disease Data found in the UCI machine learning repository consists of 14 variables measured on 303 individuals who have heart disease. The individuals had been grouped into five levels of heart disease. The information about the disease status is in the HeartDisease.target data set.

source

Author: David W. Aha (aha 'AT' ics.uci.edu) [phone]

Donors: The data was collected from the Cleveland Clinic Foundation (cleveland.data)

https://archive.ics.uci.edu/ml/datasets/Heart+Disease

Detrano, R., Janosi, A., Steinbrunn, W., Pfisterer, M., Schmid, J., Sandhu, S., Guppy, K., Lee, S., & Froelicher, V. (1989). International application of a new probability algorithm for the diagnosis of coronary artery disease. American Journal of Cardiology, 64,304--310.

David W. Aha & Dennis Kibler. "Instance-based prediction of heart-disease presence with the Cleveland database."

Gennari, J.H., Langley, P, & Fisher, D. (1989). Models of incremental concept formation. Artificial Intelligence, 40, 11--61.

Details

The variables consist of five continuous and eight discrete attributes, the former in the HeartDisease.cont data set and the later in the HeartDisease.cat data set. Three of the discrete attributes have two levels, three have three levels and two have four levels. There are six missing values in the data set.

Examples

summary(data(HeartDisease.cat))
summary(data(HeartDisease.cont))
summary(data(HeartDisease.target))