ckd: Indian Chronic Kidney Disease Data

In teigen: Model-Based Clustering and Classification with the Multivariate t Distribution

Description

This is a cleaned up version of the Chronic Kidney Disease data set available from the UCI learning repository:

http://archive.ics.uci.edu/ml/datasets/Chronic_Kidney_Disease

Nominal variables have been removed and rows with missing values recorded on the remaining variables have also been removed.

Usage

data("ckd")

Format

This data frame contains 203 rows (observations) and 13 columns (variables): 1.) ckdclass: There are 2 classes, ckd or notckd 2.) age: in years 3.) blood.pressure: in mm/Hg 4.) blood.glucose.random: in mgs/dl 5.) blood.urea: in mgs/dl 6.) serum.creatinine: in mgs/dl 7.) sodium: in mEq/L 8.) potassium: in mEq/L 9.) hemoglobin: in gms 10.) packed.cell.volume 11.) white.blood.cell.count: in cells/cmm 12.) red.blood.cell.count: in cells/cmm

Source

See http://archive.ics.uci.edu/ml/datasets/Chronic_Kidney_Disease for original source.

References

Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Examples

data(ckd)
hclustres <- cutree(hclust(dist(ckd[,-1])),3)
table(ckd[,1], hclustres)

Example output

        hclustres
           1   2   3
  ckd     47  31   1
  notckd 108  16   0

teigen documentation built on May 2, 2019, 2:51 p.m.