From National Institute of Diabetes and Digestive and Kidney Diseases.
X
is a data frame of 768 female patients with 8 attributes.
no.pregnant |
number of pregnancies. |
glucose |
plasma glucose concentration in an oral glucose tolerance test |
blood.press |
diastolic blood pressure (mm Hg) |
triceps.thick |
triceps skin fold thickness (mm) |
insulin |
2-Hour serum insulin (mu U/ml) |
BMI |
body mass index (weight in kg/(height in m)\^2) |
pedigree |
diabetes pedigree function |
y
contains the class labels: Yes
or No, for diabetic according
to WHO criteria.
The training set diabetes.tr
contains a randomly selected set of 600
subjects, and diabetes.te
contains the remaining 168 subjects.
diabetes
contains all 768 objects.
Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.
Smith, J.W., Everhart, J.E., Dickson, W.C., Knowler, W.C., & Johannes, R.S. (1988). Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In Proceedings of the Symposium on Computer Applications and Medical Care (pp. 261--265). IEEE Computer Society Press.
# NOT RUN {
attach(diabetes)
summary(X)
summary(y)
# }
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