diabetes: The Pima Indian Diabetes dataset

In dprep: Data Pre-Processing and Visualization Functions for Classification

Description

This is the Pima Indian diabetes dataset from the UCI Machine Learning Repository.

Usage

data(diabetes)

Format

A data frame with 768 observations on the following 9 variables.

V1

Number of times pregnant

V2

Plasma glucose concentration (glucose tolerance test)

V3

Diastolic blood pressure (mm Hg)

V4

Triceps skin fold thickness (mm)

V5

2-Hour serum insulin (mu U/ml)

V6

Body mass index (weight in kg/(height in m)\^2)

V7

Diabetes pedigree function

V8

Age (years)

V9

Class variable (1:tested positive for diabetes, 0: tested negative fro diabetes)

Source

The UCI Machine Learning Database Repository at:

• ftp://ftp.ics.uci.edu/pub/machine-learning-databases

• http://www.ics.uci.edu/~mlearn/MLRepository.html

Examples

#---Feature selection using SFS with the LDA classifier--
data(diabetes)
sfs(diabetes,"lda",repet=1)

Example output

Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
The best subset of features is:
[1] 7 6 3 2

dprep documentation built on May 29, 2017, 11:01 a.m.