This project involves developing a diabetes prediction model using Support Vector Machine (SVM) in Google Colab. The model is trained on the PIMA Indian Diabetes dataset, which includes features related to diabetes risk factors. The goal is to predict whether a person has diabetes based on their health data.
The dataset used is the PIMA Indian Diabetes dataset. It includes the following features:
- Pregnancies: Number of times pregnant
- Glucose: Plasma glucose concentration
- Blood Pressure: Diastolic blood pressure (mm Hg)
- Skin Thickness: Triceps skin fold thickness (mm)
- Insulin: 2-Hour serum insulin (mu U/ml)
- BMI: Body mass index (weight in kg/(height in m)^2)
- Diabetes Pedigree Function: A function that scores the likelihood of diabetes based on family history
- Age: Age of the patient (in years)
- Outcome: Target variable indicating diabetes status (0 = Non-Diabetic, 1 = Diabetic)
To run this notebook, use Google Colab and ensure you have the following libraries installed:
numpypandasscikit-learn