{"id":13738704,"url":"https://github.com/poloclub/timbertrek","last_synced_at":"2025-05-13T18:38:36.031Z","repository":{"id":56953765,"uuid":"460198208","full_name":"poloclub/timbertrek","owner":"poloclub","description":"Explore and compare 1K+ accurate decision trees in your browser!","archived":false,"fork":false,"pushed_at":"2024-03-04T18:51:27.000Z","size":38650,"stargazers_count":161,"open_issues_count":1,"forks_count":10,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-05-08T17:44:44.064Z","etag":null,"topics":["decision-tree","interactive-visualizations","interpretability","rashomon","visualization"],"latest_commit_sha":null,"homepage":"https://poloclub.github.io/timbertrek","language":"TypeScript","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/poloclub.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2022-02-16T22:25:16.000Z","updated_at":"2025-05-01T07:32:40.000Z","dependencies_parsed_at":"2024-04-22T21:08:04.255Z","dependency_job_id":null,"html_url":"https://github.com/poloclub/timbertrek","commit_stats":{"total_commits":230,"total_committers":1,"mean_commits":230.0,"dds":0.0,"last_synced_commit":"15680463d1dc32c41e9b3e8fcca48931fea5f7f3"},"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poloclub%2Ftimbertrek","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poloclub%2Ftimbertrek/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poloclub%2Ftimbertrek/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poloclub%2Ftimbertrek/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/poloclub","download_url":"https://codeload.github.com/poloclub/timbertrek/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254004913,"owners_count":21998142,"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":["decision-tree","interactive-visualizations","interpretability","rashomon","visualization"],"created_at":"2024-08-03T03:02:33.991Z","updated_at":"2025-05-13T18:38:36.002Z","avatar_url":"https://github.com/poloclub.png","language":"TypeScript","funding_links":[],"categories":["TypeScript"],"sub_categories":[],"readme":"# TimberTrek \u003ca href=\"https://poloclub.github.io/timbertrek/\"\u003e\u003cimg align=\"right\" src=\"src/imgs/timbertrek-logo-light.svg\" height=\"38\"\u003e\u003c/img\u003e\u003c/a\u003e\n\n[![Github Actions Status](https://github.com/poloclub/timbertrek/workflows/build/badge.svg)](https://github.com/poloclub/timbertrek/actions/workflows/build.yml)\n[![license](https://img.shields.io/badge/License-MIT-success)](https://github.com/poloclub/timbertrek/blob/master/LICENSE)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/poloclub/timbertrek/master?urlpath=lab/tree/notebook-widget/example/campas.ipynb)\n[![Lite](https://gist.githubusercontent.com/xiaohk/9b9f7c8fa162b2c3bc3251a5c9a799b2/raw/a7fca1d0a2d62c2b49f60c0217dffbd0fe404471/lite-badge-launch-small.svg)](https://poloclub.github.io/timbertrek/notebook)\n[![pypi](https://img.shields.io/pypi/v/timbertrek?color=blue)](https://pypi.python.org/pypi/timbertrek)\n[![arxiv badge](https://img.shields.io/badge/arXiv-2209.09227-red)](https://arxiv.org/abs/2209.09227)\n[![DOI:10.1109/VIS54862.2022.00021](https://img.shields.io/badge/DOI-10.1109/VIS54862.2022.00021-blue)](https://doi.org/10.1109/VIS54862.2022.00021)\n\nCurate decision trees that align with your knowledge and values!\n\n\u003ctable\u003e\n  \u003ctr\u003e\n    \u003ctd colspan=\"4\"\u003e\u003ca href=\"https://poloclub.github.io/timbertrek\"\u003e\u003cimg src='https://i.imgur.com/t4qtPPX.png'\u003e\u003c/a\u003e\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"https://poloclub.github.io/timbertrek\"\u003e🚀 Live Demo\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://youtu.be/3eGqTmsStJM\"\u003e📺 Demo Video\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://youtu.be/l1mr9z1TuAk\"\u003e👨🏻‍🏫 Conference Talk\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://arxiv.org/abs/2209.09227\"\u003e📖 Research Paper\u003c/a\u003e\u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\n\u003c!-- |\u003cimg src='https://i.imgur.com/t4qtPPX.png'\u003e|\n|:---:|\n|\u003ca href=\"https://youtu.be/3eGqTmsStJM\"\u003e📺 Demo Video for \"TimberTrek: Exploring and Curating Trustworthy Decision Trees with Interactive Visualization\"| --\u003e\n\n## Web Demo\n\nFor a live web demo, visit: https://poloclub.github.io/timbertrek.\n\nYou can use the web demo to explore your own Rashomon Sets! You just need to choose the `my own set` tab below the tool and upload a JSON file containing all decision paths in your Rashomon Set.\n\nCheck out this [example notebook](https://github.com/ubc-systopia/treeFarms/blob/main/treefarms/tutorial.ipynb) to see how to generate the whole Rashomon Set and the JSON file.\n\n## Notebook Demos\n\nYou can directly use TimberTrek in your favorite computational notebooks (e.g. Jupyter Notebook/Lab, Google Colab, and VS Code Notebook).\n\nCheck out three live notebook demos below.\n\n|Jupyter Lite|Binder|Google Colab|\n|:---:|:---:|:---:|\n|[![Lite](https://gist.githubusercontent.com/xiaohk/9b9f7c8fa162b2c3bc3251a5c9a799b2/raw/a7fca1d0a2d62c2b49f60c0217dffbd0fe404471/lite-badge-launch-small.svg)](https://poloclub.github.io/timbertrek/notebook)|[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/poloclub/timbertrek/master?urlpath=lab/tree/notebook-widget/example/campas.ipynb)|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1shCiDNCXy7-8XexJ65aMboZXxVBGhIZB?usp=sharing)|\n\n## Install\n\nTo use TimberTrek in a notebook, you would need to install TimberTrek with `pip`:\n\n```bash\npip install timbertrek\n```\n\n## Development\n\nClone or download this repository:\n\n```bash\ngit clone git@github.com:poloclub/timbertrek.git\n```\n\nInstall the dependencies:\n\n```bash\nnpm install\n```\n\nThen run TimberTrek:\n\n```\nnpm run dev\n```\n\nNavigate to localhost:3000. You should see TimberTrek running in your browser :)\n\n## Credits\n\nLed by \u003ca href='https://zijie.wang/' target='_blank'\u003eJay Wang\u003c/a\u003e, TimberTrek is a result of a collaboration between ML and visualization researchers from Georgia Tech, Duke University, Fujitsu Laboratories, and University of British Columbia. TimberTrek is created by \u003ca href='https://zijie.wang/' target='_blank'\u003eJay Wang\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/chudizhong' target='_blank'\u003eChudi Zhong\u003c/a\u003e, \u003ca href='https://www.linkedin.com/in/rui-xin-8070181b9' target='_blank'\u003eRui Xin\u003c/a\u003e, \u003ca href='https://scholar.google.com/citations?user=9fY1WVIAAAAJ\u0026hl=en' target='_blank'\u003eTakuya Takagi\u003c/a\u003e, \u003ca href='https://users.cs.duke.edu/~zhichen/' target='_blank'\u003eZhi Chen\u003c/a\u003e, \u003ca href='' target='_blank'\u003ePolo Chau\u003c/a\u003e, \u003ca href='https://users.cs.duke.edu/~cynthia/' target='_blank'\u003eCynthia Rudin\u003c/a\u003e, and \u003ca href='https://www.seltzer.com/margo/' target='_blank'\u003eMargo Seltzer\u003c/a\u003e.\n\n## Citation\n\nTo learn more about TimberTrek, please read our [research paper](https://arxiv.org/abs/2209.09227) (published at [IEEE VIS 2022](https://ieeevis.org/year/2022/welcome)). To learn more about the algorithm to generate the whole Rashomon set of sparse decision trees, please read our [TreeFARMS paper](https://arxiv.org/abs/2209.08040) (published at NeurIPS'22). If you find TimberTrek useful for your research, please consider citing our paper. Thanks!\n\n```bibTeX\n@inproceedings{wangTimberTrekExploringCurating2022,\n  title = {{{TimberTrek}}: {{Exploring}} and {{Curating Trustworthy Decision Trees}} with {{Interactive Visualization}}},\n  booktitle = {2022 {{IEEE Visualization Conference}} ({{VIS}})},\n  author = {Wang, Zijie J. and Zhong, Chudi and Xin, Rui and Takagi, Takuya and Chen, Zhi and Chau, Duen Horng and Rudin, Cynthia and Seltzer, Margo},\n  year = {2022}\n}\n```\n\n## License\n\nThe software is available under the [MIT License](https://github.com/poloclub/timbertrek/blob/master/LICENSE).\n\n## Contact\n\nIf you have any questions, feel free to [open an issue](https://github.com/poloclub/timbertrek/issues/new) or contact [Jay Wang](https://zijie.wang).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpoloclub%2Ftimbertrek","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpoloclub%2Ftimbertrek","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpoloclub%2Ftimbertrek/lists"}