{"id":27915393,"url":"https://github.com/nurulashraf/comparative-regression-fish-dataset","last_synced_at":"2025-05-06T15:53:51.139Z","repository":{"id":288787214,"uuid":"969176733","full_name":"nurulashraf/comparative-regression-fish-dataset","owner":"nurulashraf","description":"This analysis compares multiple linear regression and polynomial regression models using fish measurement data. It evaluates prediction accuracy through MSE, RMSE, R², and Adjusted R², and tests model performance on newly generated dummy data.","archived":false,"fork":false,"pushed_at":"2025-04-21T14:38:03.000Z","size":14339,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-21T15:37:44.627Z","etag":null,"topics":["data-science","linear-regression","machine-learning","polynomial-regression"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/nurulashraf.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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}},"created_at":"2025-04-19T15:05:38.000Z","updated_at":"2025-04-21T14:38:07.000Z","dependencies_parsed_at":"2025-04-21T15:49:46.831Z","dependency_job_id":null,"html_url":"https://github.com/nurulashraf/comparative-regression-fish-dataset","commit_stats":null,"previous_names":["nurulashraf/regression-analysis-1","nurulashraf/polynomial-linear-regression-stock-performance","nurulashraf/polynomial-linear-regression","nurulashraf/polynomial-regression","nurulashraf/comparative-regression-fish-dataset"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nurulashraf%2Fcomparative-regression-fish-dataset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nurulashraf%2Fcomparative-regression-fish-dataset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nurulashraf%2Fcomparative-regression-fish-dataset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nurulashraf%2Fcomparative-regression-fish-dataset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nurulashraf","download_url":"https://codeload.github.com/nurulashraf/comparative-regression-fish-dataset/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252717437,"owners_count":21793314,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["data-science","linear-regression","machine-learning","polynomial-regression"],"created_at":"2025-05-06T15:53:50.556Z","updated_at":"2025-05-06T15:53:51.128Z","avatar_url":"https://github.com/nurulashraf.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Fish Dataset — Multiple Linear \u0026 Polynomial Regression Comparison\n\nThis project explores and compares the performance of **Multiple Linear Regression** and **Polynomial Regression** models using a fish measurement dataset. The goal is to predict outcomes and evaluate model accuracy using metrics like **Mean Squared Error (MSE)**, **Root Mean Squared Error (RMSE)**, **R² Score**, and **Adjusted R²**. Dummy data is also generated to test model predictions beyond the original dataset.\n\n---\n\n## Project Structure\n\n- **`data/`**: Contains the dataset used for analysis and prediction.\n- **`notebooks/`**: Jupyter notebooks for data analysis, feature engineering, and model building.\n- **`README.md`**: Project overview and usage instructions.\n\n\n---\n\n## Features\n\n- Compares **Multiple Linear Regression** and **Polynomial Regression** on the same dataset.\n- Uses real-world fish measurement data for training and testing.\n- Generates dummy data to test model predictions.\n- Outputs key evaluation metrics: MSE, RMSE, R², and Adjusted R².\n- Saves trained models for reuse.\n\n---\n\n## Tools \u0026 Libraries\n\n- Python  \n- Pandas  \n- NumPy  \n- Scikit-learn  \n- Matplotlib  \n- Joblib  \n\n---\n\n## How to Use\n\n1. Clone this repository:\n    ```bash\n    git clone https://github.com/nurulashraf/comparative-regression-fish-dataset.git\n    cd comparative-regression-fish-dataset\n    ```\n\n2. Install the required Python packages:\n    ```bash\n    pip install pandas numpy scikit-learn matplotlib joblib\n    ```\n\n3. Open the Jupyter notebook:\n    ```bash\n    jupyter notebook comparative_regression_fish_dataset.ipynb\n    ```\n\n4. Run through the notebook to:\n    - Train both models.\n    - Evaluate performance.\n    - Generate predictions for dummy data.\n    - Save or load pre-trained models using `joblib`.\n\n---\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnurulashraf%2Fcomparative-regression-fish-dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnurulashraf%2Fcomparative-regression-fish-dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnurulashraf%2Fcomparative-regression-fish-dataset/lists"}