{"id":13486977,"url":"https://github.com/jundongl/scikit-feature","last_synced_at":"2025-05-15T14:05:22.185Z","repository":{"id":40910954,"uuid":"45693656","full_name":"jundongl/scikit-feature","owner":"jundongl","description":"open-source feature selection repository in python","archived":false,"fork":false,"pushed_at":"2024-07-11T09:07:01.000Z","size":199520,"stargazers_count":1539,"open_issues_count":45,"forks_count":443,"subscribers_count":60,"default_branch":"master","last_synced_at":"2025-05-09T07:09:21.918Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jundongl.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}},"created_at":"2015-11-06T16:34:33.000Z","updated_at":"2025-05-09T07:08:51.000Z","dependencies_parsed_at":"2024-09-20T16:12:08.290Z","dependency_job_id":null,"html_url":"https://github.com/jundongl/scikit-feature","commit_stats":{"total_commits":77,"total_committers":5,"mean_commits":15.4,"dds":0.1298701298701299,"last_synced_commit":"48cffad4e88ff4b9d2f1c7baffb314d1b3303792"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jundongl%2Fscikit-feature","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jundongl%2Fscikit-feature/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jundongl%2Fscikit-feature/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jundongl%2Fscikit-feature/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jundongl","download_url":"https://codeload.github.com/jundongl/scikit-feature/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254355334,"owners_count":22057354,"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":[],"created_at":"2024-07-31T18:00:53.986Z","updated_at":"2025-05-15T14:05:17.176Z","avatar_url":"https://github.com/jundongl.png","language":"Python","funding_links":[],"categories":["The Data Science Toolbox","Feature Engineering","Table of Contents","Feature Extraction"],"sub_categories":["General Machine Learning Packages","Feature Selection","General Feature Extraction"],"readme":"scikit-feature\n===============================\nFeature selection repository scikit-feature in Python. \n\nscikit-feature is an open-source feature selection repository in Python developed by Data Mining and Machine Learning Lab at Arizona State University. It is built upon one widely used machine learning package scikit-learn and two scientific computing packages Numpy and Scipy. scikit-feature contains around 40 popular feature selection algorithms, including traditional feature selection algorithms and some structural and streaming feature selection algorithms. \n\nIt serves as a platform for facilitating feature selection application, research and comparative study. It is designed to share widely used feature selection algorithms developed in the feature selection research, and offer convenience for researchers and practitioners to perform empirical evaluation in developing new feature selection algorithms.\n\n## Installing scikit-feature\n### Prerequisites:\nPython 2.7 *and Python 3*\n\nNumPy\n\nSciPy\n\nScikit-learn\n\n### Steps:\nFor Linux users, you can install the repository by the following command:\n\n    python setup.py install\n\nFor Windows users, you can also install the repository by the following command:\n\n    setup.py install\n\n## Project website\nInstructions of using this repository can be found in our project webpage at http://featureselection.asu.edu/\n\n## Citation\n\nIf you find scikit-feature feature selection reposoitory useful in your research, please consider citing the following paper::\n\n    @article{li2018feature,\n    title={Feature selection: A data perspective},\n    author={Li, Jundong and Cheng, Kewei and Wang, Suhang and Morstatter, Fred and Trevino, Robert P and Tang, Jiliang and Liu, Huan},\n    journal={ACM Computing Surveys (CSUR)},\n    volume={50},\n    number={6},\n    pages={94},\n    year={2018},\n    publisher={ACM}\n    }\n    \n## Contact\nJundong Li\nE-mail: jundong@virgnia.edu\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjundongl%2Fscikit-feature","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjundongl%2Fscikit-feature","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjundongl%2Fscikit-feature/lists"}