{"id":24396138,"url":"https://github.com/ad1tyaraj/heart-attack-model","last_synced_at":"2026-04-11T13:33:53.726Z","repository":{"id":282149340,"uuid":"929720248","full_name":"Ad1tyaRaj/Heart-Attack-Model","owner":"Ad1tyaRaj","description":"This repository contains a machine learning project that predicts the likelihood of a heart attack based on a dataset of 170,501 rows and 25 features. The current model achieves an accuracy of 75%, with ongoing improvements through feature engineering and scaling.","archived":false,"fork":false,"pushed_at":"2025-02-09T08:21:04.000Z","size":4336,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-30T22:33:30.769Z","etag":null,"topics":["apps","django","flask","framework","python","webapps"],"latest_commit_sha":null,"homepage":"https://ad1tyaraj.github.io/Portfolio/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Ad1tyaRaj.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-02-09T08:17:07.000Z","updated_at":"2025-02-09T14:03:36.000Z","dependencies_parsed_at":"2025-03-13T05:01:00.187Z","dependency_job_id":null,"html_url":"https://github.com/Ad1tyaRaj/Heart-Attack-Model","commit_stats":null,"previous_names":["ad1tyaraj/heart-attack-model"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Ad1tyaRaj/Heart-Attack-Model","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ad1tyaRaj%2FHeart-Attack-Model","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ad1tyaRaj%2FHeart-Attack-Model/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ad1tyaRaj%2FHeart-Attack-Model/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ad1tyaRaj%2FHeart-Attack-Model/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Ad1tyaRaj","download_url":"https://codeload.github.com/Ad1tyaRaj/Heart-Attack-Model/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ad1tyaRaj%2FHeart-Attack-Model/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31682953,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-11T13:07:20.380Z","status":"ssl_error","status_checked_at":"2026-04-11T13:06:47.903Z","response_time":54,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["apps","django","flask","framework","python","webapps"],"created_at":"2025-01-19T21:25:21.401Z","updated_at":"2026-04-11T13:33:53.708Z","avatar_url":"https://github.com/Ad1tyaRaj.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Heart Attack Prediction Model\n\n## Overview\nThis repository contains a machine learning project that predicts the likelihood of a heart attack based on a dataset of 170,501 rows and 25 features. The current model achieves an accuracy of **75%**, with ongoing improvements through feature engineering and scaling.\n\n## Features\n- **Dataset Size**: 170,501 rows and 25 columns.\n- **Model Accuracy**: 75%.\n- **Techniques Used**:\n  - Feature Engineering: Enhancing feature selection and transformation.\n  - Scaling: Standardizing feature values for better model performance.\n\n## Objectives\n1. Improve the model's accuracy and robustness.\n2. Optimize feature selection and scaling techniques.\n3. Provide a user-friendly interface and detailed documentation.\n\n## Project Structure\n```\nHeartAttackPrediction/\n│\n├── data/                   # Dataset files\n├── notebooks/              # Jupyter notebooks for data analysis and modeling\n├── Heart_Attack_test1/     # Source code for data processing and model training\n├── Heart_Attack_70/        # Saved trained models\n├── README.md               # Project documentation\n└── requirements.txt        # Python dependencies\n```\n\n## Feature Engineering and Scaling\n1. **Current Focus**:\n   - Identifying redundant or irrelevant features.\n   - Transforming features (e.g., normalization, log transformation).\n   - Encoding categorical variables.\n2. **Scaling**:\n   - StandardScaler for numerical features.\n   - RobustScaler to handle outliers.\n\n## Future Goals\n- Improve accuracy to 90% or higher.\n- Experiment with ensemble methods (e.g., Random Forest, Gradient Boosting).\n- Deploy the model using a web app (e.g., Flask, FastAPI).\n- Conduct hyperparameter tuning for further optimization.\n\n## Installation\n1. Clone this repository:\n   ```bash\n   git clone https://github.com/yourusername/HeartAttackPrediction.git\n   cd HeartAttackPrediction\n   ```\n2. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n3. Run the model:\n   ```bash\n   python src/train_model.py\n   ```\n\n## Usage\n1. Add your dataset to the `data/` directory.\n2. Use the provided Jupyter notebooks for data analysis and feature engineering.\n3. Train the model with the command above or customize the pipeline as needed.\n\n## Acknowledgments\n- **Dataset Source**: [Include dataset link/source if applicable].\n- **Contributions**: Feel free to contribute via pull requests or open issues for feedback and suggestions.\n\n## License\nThis project is licensed under the [MIT License](LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fad1tyaraj%2Fheart-attack-model","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fad1tyaraj%2Fheart-attack-model","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fad1tyaraj%2Fheart-attack-model/lists"}