{"id":28907958,"url":"https://github.com/jahanostg/linear-regression_ml-algorithm","last_synced_at":"2026-05-08T05:12:01.258Z","repository":{"id":299833131,"uuid":"1004161497","full_name":"jahanOSTG/Linear-Regression_ML-Algorithm","owner":"jahanOSTG","description":"Linear Regression Algorithm","archived":false,"fork":false,"pushed_at":"2025-06-18T14:53:45.000Z","size":147,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-18T15:19:34.779Z","etag":null,"topics":["colab-notebook","matplotlib","numpy","pandas","scikit-learn","seaborn"],"latest_commit_sha":null,"homepage":"","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/jahanOSTG.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}},"created_at":"2025-06-18T07:56:13.000Z","updated_at":"2025-06-18T15:07:56.000Z","dependencies_parsed_at":"2025-06-18T15:19:36.477Z","dependency_job_id":"1c0896eb-9b0b-42d5-81b7-932169ec042b","html_url":"https://github.com/jahanOSTG/Linear-Regression_ML-Algorithm","commit_stats":null,"previous_names":["jahanostg/ml-algorithm1_linear-regression"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jahanOSTG/Linear-Regression_ML-Algorithm","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jahanOSTG%2FLinear-Regression_ML-Algorithm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jahanOSTG%2FLinear-Regression_ML-Algorithm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jahanOSTG%2FLinear-Regression_ML-Algorithm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jahanOSTG%2FLinear-Regression_ML-Algorithm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jahanOSTG","download_url":"https://codeload.github.com/jahanOSTG/Linear-Regression_ML-Algorithm/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jahanOSTG%2FLinear-Regression_ML-Algorithm/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261153705,"owners_count":23116918,"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":["colab-notebook","matplotlib","numpy","pandas","scikit-learn","seaborn"],"created_at":"2025-06-21T16:06:51.334Z","updated_at":"2026-05-08T05:12:01.250Z","avatar_url":"https://github.com/jahanOSTG.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"#  Linear Regression on Custom Dataset\n\nThis repository demonstrates a full linear regression workflow using a dataset.\n\n---\n\n\n\n##  Dataset Overview\n\nThe dataset (`friend.csv`) contains the following columns:\n\n| Column | Description                               |\n|--------|-------------------------------------------|\n| ID     | Unique identifier (ignored)               |\n| size   | Custom feature (e.g., test score, item size, etc.) |\n| Age    | Age of the individual                     |\n| prize  | Prize or cost-related value               |\n| Number | 🎯 Target variable                         |\n\n---\n\n## ✅ Steps Performed\n\n### 1. Mount Google Drive  \nTo access the dataset stored in Google Drive.\n\n### 2. Import Libraries  \nUsed libraries:\n- `pandas`\n- `numpy`\n- `matplotlib`\n- `seaborn`\n- `scikit-learn`\n\n### 3. Load and Preprocess Data  \n- Removed unnecessary columns (`ID`, if not useful).  \n- Handled whitespace in column names.  \n- One-hot encoding skipped as no categorical columns exist.\n\n### 4. Train-Test Split  \nSplit the data into training and testing sets using `train_test_split()`.\n\n### 5. Train Model  \nTrained a `LinearRegression()` model on the training data.\n\n### 6. Prediction \u0026 Evaluation  \n- Generated predictions on the test set.  \n- Calculated **MAE**, **MSE**, **RMSE**, and **R²** for performance analysis.\n\n  \n### 7. Visualization  \n-  **Regression Line Plot** to compare actual vs predicted values.  \n-  **Residual Plot** to check errors.  \n-  **Heatmap** to show correlation between all numeric features.\n\n---\n\n\n  \n  ## About **Linear Regression**\n  ### Advantages\n  - Simple to implement and efficient to train\n  - Overfitting can be reduced by regularization\n  - Performs well when the dataset is linearly separable.\n\n  ### Disadvantages\n  - Assumes that the data is independent which is rare in real life\n  - Prone to noise and overfitting\n  - Sensitive to outliers. \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjahanostg%2Flinear-regression_ml-algorithm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjahanostg%2Flinear-regression_ml-algorithm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjahanostg%2Flinear-regression_ml-algorithm/lists"}