Diabetes

Diabetes Prediction Dataset This dataset contains medical diagnostic measurements for 768 female patients, used to predict the onset of diabetes. The data includes various physiological factors and a class variable that indicates whether or not a patient has diabetes. The dataset is structured as follows: Pregnancies: Number of times the patient has been pregnant. Glucose: Plasma glucose concentration (mg/dL) after 2 hours in an oral glucose tolerance test. BloodPressure: Diastolic blood pressure (mm Hg). SkinThickness: Triceps skinfold thickness (mm). Insulin: 2-Hour serum insulin (mu U/ml). BMI: Body mass index, calculated as weight in kg/(height in m)^2. DiabetesPedigreeFunction: A function which scores the likelihood of diabetes based on family history. Age: Age of the patient in years. Outcome: Binary variable (0 or 1) indicating whether the patient has diabetes (1) or not (0). Usage: This dataset is widely used for training machine learning models to predict the likelihood of diabetes. It's suitable for binary classification tasks, and can be utilized for projects in data science, healthcare analytics, and machine learning education