{"id":25856740,"url":"https://github.com/tim-raphael/lrt-concept","last_synced_at":"2025-08-03T09:04:20.402Z","repository":{"id":221994022,"uuid":"755971108","full_name":"Tim-Raphael/lrt-concept","owner":"Tim-Raphael","description":"This tool implements a simple linear regression algorithm as a proof of concept. It is designed to perform linear regression given a dataset and a target value, returning the predicted value, slope, and intercept.","archived":false,"fork":false,"pushed_at":"2024-02-11T16:23:03.000Z","size":140,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-02-11T17:28:10.383Z","etag":null,"topics":["algorithms","linear-regression","rust","web-assembly"],"latest_commit_sha":null,"homepage":"https://tim-raphael.github.io/lrt-concept/demo/","language":"Rust","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/Tim-Raphael.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}},"created_at":"2024-02-11T16:11:00.000Z","updated_at":"2024-02-11T17:28:12.861Z","dependencies_parsed_at":"2024-02-11T17:28:12.580Z","dependency_job_id":"2be8837d-a85c-4020-8a9c-4bf00635ccdc","html_url":"https://github.com/Tim-Raphael/lrt-concept","commit_stats":null,"previous_names":["tim-raphael/lrt-concept"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tim-Raphael%2Flrt-concept","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tim-Raphael%2Flrt-concept/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tim-Raphael%2Flrt-concept/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tim-Raphael%2Flrt-concept/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Tim-Raphael","download_url":"https://codeload.github.com/Tim-Raphael/lrt-concept/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241406776,"owners_count":19958038,"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":["algorithms","linear-regression","rust","web-assembly"],"created_at":"2025-03-01T18:27:56.933Z","updated_at":"2025-03-01T18:27:58.075Z","avatar_url":"https://github.com/Tim-Raphael.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Simple Linear Regression Tool (Proof of Concept)\n\nThis tool implements a simple linear regression algorithm as a proof of concept. It is designed to perform linear regression given a dataset and a target value, returning the predicted value, slope, and intercept.\n\n## Formula Explanation\n\nThe linear regression formula predicts the value of a dependent variable based on the value of an independent variable. It assumes a linear relationship between the variables and is represented by the equation:\n\n $ȳ = (1/n) Σ yi$\n\n $x̄ = (1/n) Σ xi$\n\n $m = Σ((xi - x̄) * (yi - ȳ)) / Σ((xi - x̄)^2)$\n\n $b = ȳ - m * x̄$\n\n $y = mx + b$\n \n\n### Variables Explanation:\n\n- **Dependent Variable $( y )$**:\n  - Represents the variable we aim to predict based on the independent variable $x$. It is often referred to as the predicted value.\n\n- **Independent Variable $( x )$**:\n  - Denotes the variable used to make predictions about the dependent variable $y$. It serves as the input to our model or predictor variable.\n\n- **Slope $( m )$**:\n  - Indicates the rate of change of the dependent variable $y$ concerning the independent variable $x$. It shows how much $y$ changes for a unit change in $x$.\n  - A positive slope $m$ suggests a positive relationship between $x$ and $y$, while a negative slope suggests a negative relationship.\n\n- **Intercept $( b )$**:\n  - Represents the point where the regression line intersects the y-axis when $x = 0$. It indicates the value of $y$ when $x$ is zero and signifies the baseline value of $y$ when all other factors are zero.\n\n## Demo\n\nThe tool takes a dataset consisting of pairs of $[ x, y ]$ values and a target value $x$. It performs simple linear regression on the dataset and returns the predicted value, slope, and intercept.\n\n### Input\n\n- `dataset`: A vector of $[x, y]$ pairs representing the dataset.\n- `target`: The target value for which the prediction is to be made.\n\n### Output\n\n- Predicted value: The predicted value of the dependent variable $y$ for the given target value $x$.\n- Slope: The slope of the regression line.\n- Intercept: The intercept of the regression line.\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\nFeel free to contribute, report issues, or suggest improvements.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftim-raphael%2Flrt-concept","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftim-raphael%2Flrt-concept","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftim-raphael%2Flrt-concept/lists"}