HAWKING007/diabeties

Diabetic Prediction Model

Model Description

This model predicts the likelihood of diabetes based on various health metrics. It uses a trained Support Vector Machine (SVM) model and standard scaling.

Inputs and Outputs

Input Features

• Pregnancies: Number of pregnancies.
• Glucose: Plasma glucose concentration.
• 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 in years.

Output

• Diabetes Prediction: Boolean value (True if diabetes is predicted, False otherwise).
• Probability: Confidence score of the prediction (0 to 1).

Example Input

input_data = {
    "Pregnancies": 2,
    "Glucose": 120,
    "BloodPressure": 70,
    "SkinThickness": 30,
    "Insulin": 100,
    "BMI": 25.6,
    "DiabetesPedigreeFunction": 0.5,
    "Age": 31
}