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Description:

A population of women who were at least 21 years old, of Pima Indian heritage and living near Phoenix, Arizona, was tested for diabetes according to World Health Organization criteria. The data were collected by the US National Institute of Diabetes and Digestive and Kidney Diseases. We used the 532 complete records after dropping the (mainly missing) data on serum insulin.

Variables:

These data frames contains the following columns:

npreg

number of pregnancies.

glu

plasma glucose concentration in an oral glucose tolerance test.

bp

diastolic blood pressure (mm Hg).

skin

triceps skin fold thickness (mm).

bmi

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

ped

diabetes pedigree function.

age

age in years.

type

Yes or No, for diabetic according to WHO criteria.

Details

The training set Pima.tr contains a randomly selected set of 200 subjects, and Pima.te contains the remaining 332 subjects. Pima.tr2 contains Pima.tr plus 100 subjects with missing values in the explanatory variables.

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Columns:

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References/Notes/Attributions:

Source

Smith, J. W., Everhart, J. E., Dickson, W. C., Knowler, W. C. and Johannes, R. S. (1988) Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In Proceedings of the Symposium on Computer Applications in Medical Care (Washington, 1988), ed. R. A. Greenes, pp. 261–265. Los Alamitos, CA: IEEE Computer Society Press.

Ripley, B.D. (1996) Pattern Recognition and Neural Networks. Cambridge: Cambridge University Press.

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