Predicting Diabetes with Multilayer Perceptrons
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.
Columns
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PregnanciesNumber of times pregnant
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GlucosePlasma glucose concentration a 2 hours in an oral glucose tolerance test
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BloodPressureDiastolic blood pressure (mm Hg)
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SkinThicknessTriceps skin fold thickness (mm)
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Insulin2-Hour serum insulin (mu U/ml)
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BMIBody mass index (weight in kg/(height in m)^2)
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DiabetesPedigreeFunctionDiabetes pedigree function
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AgeAge (years)
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OutcomeClass variable (0 or 1) 268 of 768 are 1, the others are 0