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The dataset used in this project is originally from NIDDK. The objective is to predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset.

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Diabetes-prediction

The dataset used in this project is originally from NIDDK. The objective is to predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset.

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 more.

  • Pregnancies: Number of times pregnant
  • Glucose: Plasma glucose concentration in an oral glucose tolerance test
  • BloodPressure: Diastolic blood pressure (mm Hg)
  • SkinThickness: Triceps skinfold thickness (mm)
  • Insulin: Two hour serum insulin
  • BMI: Body Mass Index
  • DiabetesPedigreeFunction: Diabetes pedigree function
  • Age: Age in years
  • Outcome: Class variable (either 0 or 1). 268 of 768 values are 1, and the others are 0

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The dataset used in this project is originally from NIDDK. The objective is to predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset.

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