{"id":24688635,"url":"https://github.com/chandkund/predicting-diabetes-onset","last_synced_at":"2026-04-13T04:47:37.171Z","repository":{"id":271920065,"uuid":"850793385","full_name":"chandkund/Predicting-Diabetes-Onset","owner":"chandkund","description":"The \"Predicting Diabetes Onset\" project aims to build a machine learning model that predicts whether an individual has diabetes based on various health-related features. 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The goal is to develop a predictive model based on health-related features to determine the likelihood of diabetes.\n\n## Dataset\nThe dataset includes the following features:\n- **Pregnancies**: Number of pregnancies  🤰\n- **Glucose**: Plasma glucose concentration (2 hours in an oral glucose tolerance test)  🩸 \n- **BloodPressure**: Diastolic blood pressure (mm Hg)  💉\n- **SkinThickness**: Triceps skin fold thickness (mm)  📏\n- **Insulin**: 2-Hour serum insulin (mu U/ml)  🧪\n- **BMI**: Body mass index (weight in kg/(height in m)^2) ⚖️\n- **DiabetesPedigreeFunction**: A measure of likelihood of diabetes based on family history.     \n- **Age**: Age of the individual (years)  🎂\n- **Outcome**: Whether the individual has diabetes (1) or not (0) ✅❌\n \n## Models Used\n- **GaussianNB**\n- **DecisionTreeClassifier**\n- **RandomForestClassifier**\n- **LogisticRegression**\n- **AdaBoostClassifier**\n- **XGBClassifier**\n- **SVC**\n- **GradientBoostingClassifier**\n- **Neural Network**\n\n## Installation\nTo run this project, you need to install the following Python libraries:\n- pandas  📜\n- numpy  🧮\n- scikit-learn  🛠️\n- xgboost  🚀\n- tensorflow (for Neural Networks) 🧠\n\nYou can install them using pip:\n```bash\npip install pandas numpy scikit-learn xgboost tensorflow\n```\n\n## Usage\nClone the repository:\n```bash\ngit clone https://github.com/chandkund/Predicting-Diabetes-Onset\n```\n## Navigate to the project directory:\n```bash\ncd Predicting-Diabetes-Onset\n```\n## Run the main script:\n```bash\npython main.py\n```\nResults\nThe project evaluates the performance of various models on the dataset, providing insights into which model performs best for predicting diabetes onset.\n\nLicense\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE)file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchandkund%2Fpredicting-diabetes-onset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchandkund%2Fpredicting-diabetes-onset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchandkund%2Fpredicting-diabetes-onset/lists"}