ctg {diversityForest}R Documentation

Data on automatic analysis of cardiotocograms

Description

This data set contains measurements from 2126 fetal cardiotocograms (CTGs). The CTGs were automatically processed and the respective diagnostic features measured. The CTGs were also classified by three expert obstetricians and a consensus classification label assigned to each of them. This description is taken from the UC Irvine Machine Learning Repository, where this data set was downloaded from. The outcome CLASS is categorical with ten classes that correspond to different fetal heart rate patterns. See the 'Details' section below for further information.

Format

A data frame with 2126 observations, 24 covariates and one 10-class outcome variable

Details

The variables are as follows:

⁠ ⁠
The classes of the outcome CLASS are as follows:

This is a pre-processed version of the "Cardiotocography" data set published in the UC Irvine Machine Learning Repository. The raw data contained the four additional variables Date, FileName, SegFile, and NSP, which were removed in this version of the data. Moreover, the variable DR, representing the number of repetitive decelerations per second was removed as well because it was 0 for all observations.

Source

UC Irvine Machine Learning Repository, link: https://archive.ics.uci.edu/dataset/193/cardiotocography/ (Accessed: 29/08/2024)

References

Examples


# Load data:
data(ctg)

# Numbers of observations per outcome class:
table(ctg$CLASS)

# Dimension of data:
dim(ctg)

# First rows of data:
head(ctg) 


[Package diversityForest version 0.6.0 Index]