"This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset
is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset."
This data set is from www.kaggle.com. The original notes on the website state:
Context
"This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset
is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset.
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."
Content
"The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the
number of pregnancies the patient has had, their BMI, insulin level, age, and so on.
Acknowledgements
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.- Pregnancies
Number of time pregnant
- Glucose
Plasma glucose concentration a 2 hours in an oral glucose tolerance test
- BloodPressure
Diastolic blood pressure (mm Hg)
- SkinThickness
Triceps skin fold thickness (mm)
- Insulin
2-Hour serum insulin (mu U/ml)
- BMI
Body mass index (weight in kg/(height in m)^2)
- DiabetesPedigreeFunction
Diabetes pedigree function
- Age
Age (years)
- Outcome
Class variable (0 or 1) 268 of 768 are 1, the others are 0