{"id":23629674,"url":"https://github.com/junya737/weighted-pls-regression","last_synced_at":"2026-04-17T00:02:18.745Z","repository":{"id":269942483,"uuid":"908909896","full_name":"junya737/weighted-pls-regression","owner":"junya737","description":"A Python implementation of Weighted Partial Least Squares Regression with support for sample weights.","archived":false,"fork":false,"pushed_at":"2025-02-12T09:09:03.000Z","size":8,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-14T11:50:56.840Z","etag":null,"topics":["machine-learning","partial-least-squares-regression","scikit-learn"],"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/junya737.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":"2024-12-27T09:13:43.000Z","updated_at":"2025-02-12T08:56:06.000Z","dependencies_parsed_at":"2025-05-19T03:32:26.277Z","dependency_job_id":null,"html_url":"https://github.com/junya737/weighted-pls-regression","commit_stats":null,"previous_names":["junya737/weighted-pls-regression"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/junya737/weighted-pls-regression","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junya737%2Fweighted-pls-regression","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junya737%2Fweighted-pls-regression/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junya737%2Fweighted-pls-regression/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junya737%2Fweighted-pls-regression/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/junya737","download_url":"https://codeload.github.com/junya737/weighted-pls-regression/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junya737%2Fweighted-pls-regression/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31909235,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-16T18:22:33.417Z","status":"ssl_error","status_checked_at":"2026-04-16T18:21:47.142Z","response_time":69,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 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":["machine-learning","partial-least-squares-regression","scikit-learn"],"created_at":"2024-12-28T01:16:45.992Z","updated_at":"2026-04-17T00:02:18.727Z","avatar_url":"https://github.com/junya737.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# weighted-pls-regression\n\n## Overview\n\nThis project implements Weighted Partial Least Squares (WPLS) Regression, a method that incorporates sample weights into the standard PLS regression model.\n\n**Author:** Junya Ihira  \n**Release Date:** December 27, 2024  \n\n## Motivation\n\nThe default PLSRegression implementation in scikit-learn does not support sample weights. I couldn't also find Python implementations with sample weights.\n\n\n## Environment\n\nThis implementation has been tested in the following environment:\n- OS: Ubuntu 22.04.4 LTS\n- Python: 3.10.14\n- Libraries:\n    - numpy: 1.26.4\n\t- scikit-learn: 1.5.0\n\n## Features\n- Supports sample weights for flexible regression modeling.\n- Compatible with scikit-learn’s API, enabling integration into pipelines.\n\n\n## Limitation\n- Standardization Toggle: \nCurrently, standardization cannot be turned off. \nThis feature may be added in future updates.\n\n## Tutorial\n\nA tutorial (tutorial.ipynb) shows how to use this implementation and compares it with scikit-learn’s PLSRegression.\nIn my environment, the results (MSE, coefficients, intercepts) matched.\n\n\n## License\nThis project is licensed under the MIT License.\n\n## Contact\nFor questions, suggestions, or bug reports, please feel free to:\n- Open an issue.\n- Email me (junyaihira[@]gmail.com).\n\nYour feedback is highly appreciated!\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjunya737%2Fweighted-pls-regression","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjunya737%2Fweighted-pls-regression","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjunya737%2Fweighted-pls-regression/lists"}