I developed a machine learning projects that predict diabetes using health data from people who have lived in Pima Arizona. I used the Random Forest Classification method in this project
One of the most important issues here is that all our patients are at least 21 years old to prevent diabetes that will occur at a young age.
I shared the data set with the code. You can use it as you wish.
- Pregnancies: Number of times 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)
The target label indicates whether the patient has been diagnosed with diabetes (1) or not (0).