This dataset is a collection of data focused on predicting diabetes. Each row of data includes information about several relevant health attributes, such as the number of pregnancies, glucose level in the blood plasma, blood pressure, skinfold thickness, insulin level, body mass index (BMI), diabetes pedigree function index, age, and a final label indicating whether the individual has been diagnosed with diabetes or not.
The attributes available in this dataset are:
- Pregnancies: Number of pregnancies experienced by the individual.
- Glucose: Glucose level in the blood plasma.
- BloodPressure: Systolic and diastolic blood pressure.
- SkinThickness: Skinfold thickness.
- Insulin: Insulin level in serum.
- BMI: Body mass index.
- DiabetesPedigreeFunction: Diabetes pedigree function index.
- Age: Individual's age.
- Outcome: Label indicating whether the individual has diabetes or not (0 for no, 1 for yes).
This dataset can be used to develop machine learning models that predict the risk of diabetes based on the provided health attributes. With proper analysis and accurate model development, this dataset can help in early diagnosis and management of diabetes.