{"id":13665715,"url":"https://github.com/tensorflow/decision-forests","last_synced_at":"2025-05-14T01:07:30.663Z","repository":{"id":37699357,"uuid":"360551298","full_name":"tensorflow/decision-forests","owner":"tensorflow","description":"A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.","archived":false,"fork":false,"pushed_at":"2025-04-02T15:03:14.000Z","size":6139,"stargazers_count":675,"open_issues_count":41,"forks_count":113,"subscribers_count":22,"default_branch":"main","last_synced_at":"2025-04-03T08:03:29.768Z","etag":null,"topics":["decision-forest","decision-trees","gradient-boosting","interpretability","keras","machine-learning","ml","python","random-forest","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tensorflow.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","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":"2021-04-22T14:37:50.000Z","updated_at":"2025-04-02T15:03:19.000Z","dependencies_parsed_at":"2023-02-14T01:15:20.900Z","dependency_job_id":"ecb63919-c5c9-40fa-a7e7-8b8127bdeca5","html_url":"https://github.com/tensorflow/decision-forests","commit_stats":{"total_commits":582,"total_committers":40,"mean_commits":14.55,"dds":0.5893470790378007,"last_synced_commit":"16c057f9fa26660a4d68ed2bedf92ca8e7bed3de"},"previous_names":[],"tags_count":36,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorflow%2Fdecision-forests","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorflow%2Fdecision-forests/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorflow%2Fdecision-forests/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorflow%2Fdecision-forests/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tensorflow","download_url":"https://codeload.github.com/tensorflow/decision-forests/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248224820,"owners_count":21068075,"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-forest","decision-trees","gradient-boosting","interpretability","keras","machine-learning","ml","python","random-forest","tensorflow"],"created_at":"2024-08-02T06:00:48.306Z","updated_at":"2025-04-10T13:09:41.132Z","avatar_url":"https://github.com/tensorflow.png","language":"Python","readme":"\u003cp align=\"center\"\u003e\n\u003cimg src=\"documentation/image/logo.png\"  /\u003e\n\u003c/p\u003e\n\n**TensorFlow Decision Forests** (**TF-DF**) is a library to train, run and\ninterpret [decision forest](https://ydf.readthedocs.io/en/latest/intro_df.html)\nmodels (e.g., Random Forests, Gradient Boosted Trees) in TensorFlow. TF-DF\nsupports classification, regression and ranking.\n\n**TF-DF** is powered by\n[Yggdrasil Decision Forest](https://github.com/google/yggdrasil-decision-forests)\n(**YDF**, a library to train and use decision forests in C++, JavaScript, CLI,\nand Go. TF-DF models are\n[compatible](https://ydf.readthedocs.io/en/latest/convert_model.html#convert-a-a-tensorflow-decision-forests-model-to-a-yggdrasil-model)\nwith YDF' models, and vice versa.\n\nTensorflow Decision Forests is available on Linux and Mac. Windows users can use\nthe library through WSL+Linux.\n\n## Usage example\n\nA minimal end-to-end run looks as follows:\n\n```python\nimport tensorflow_decision_forests as tfdf\nimport pandas as pd\n\n# Load the dataset in a Pandas dataframe.\ntrain_df = pd.read_csv(\"project/train.csv\")\ntest_df = pd.read_csv(\"project/test.csv\")\n\n# Convert the dataset into a TensorFlow dataset.\ntrain_ds = tfdf.keras.pd_dataframe_to_tf_dataset(train_df, label=\"my_label\")\ntest_ds = tfdf.keras.pd_dataframe_to_tf_dataset(test_df, label=\"my_label\")\n\n# Train the model\nmodel = tfdf.keras.RandomForestModel()\nmodel.fit(train_ds)\n\n# Look at the model.\nmodel.summary()\n\n# Evaluate the model.\nmodel.evaluate(test_ds)\n\n# Export to a TensorFlow SavedModel.\n# Note: the model is compatible with Yggdrasil Decision Forests.\nmodel.save(\"project/model\")\n```\n\n## Google I/O Presentation\n\n\u003cdiv align=\"center\"\u003e\n    \u003ca href=\"https://youtu.be/5qgk9QJ4rdQ\"\u003e\n        \u003cimg src=\"https://img.youtube.com/vi/5qgk9QJ4rdQ/0.jpg\"\u003e\u003c/img\u003e\n    \u003c/a\u003e\n\u003c/div\u003e\n\n## Documentation \u0026 Resources\n\nThe following resources are available:\n\n-   [TF-DF on TensorFlow.org](https://tensorflow.org/decision_forests) (API\n    Reference, Guides and Tutorials)\n-   [Tutorials](https://www.tensorflow.org/decision_forests/tutorials) (on\n    tensorflow.org)\n-   [YDF documentation](https://ydf.readthedocs.io) (also applicable to TF-DF)\n-   [Issue tracker](https://github.com/tensorflow/decision-forests/issues)\n-   [Known issues](documentation/known_issues.md)\n-   [Changelog](CHANGELOG.md)\n-   [More examples](documentation/more_examples.md)\n\n## Installation\n\nTo install TensorFlow Decision Forests, run:\n\n```shell\npip3 install tensorflow_decision_forests --upgrade\n```\n\nSee the [installation](documentation/installation.md) page for more details,\ntroubleshooting and alternative installation solutions.\n\n## Contributing\n\nContributions to TensorFlow Decision Forests and Yggdrasil Decision Forests are\nwelcome. If you want to contribute, make sure to review the\n[developer manual](documentation/developer_manual.md) and\n[contribution guidelines](CONTRIBUTING.md).\n\n## Citation\n\nIf you us Tensorflow Decision Forests in a scientific publication, please cite\nthe following paper:\n[Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library](https://doi.org/10.1145/3580305.3599933).\n\n**Bibtex**\n\n```\n@inproceedings{GBBSP23,\n  author       = {Mathieu Guillame{-}Bert and\n                  Sebastian Bruch and\n                  Richard Stotz and\n                  Jan Pfeifer},\n  title        = {Yggdrasil Decision Forests: {A} Fast and Extensible Decision Forests\n                  Library},\n  booktitle    = {Proceedings of the 29th {ACM} {SIGKDD} Conference on Knowledge Discovery\n                  and Data Mining, {KDD} 2023, Long Beach, CA, USA, August 6-10, 2023},\n  pages        = {4068--4077},\n  year         = {2023},\n  url          = {https://doi.org/10.1145/3580305.3599933},\n  doi          = {10.1145/3580305.3599933},\n}\n```\n\n**Raw**\n\nYggdrasil Decision Forests: A Fast and Extensible Decision Forests Library,\nGuillame-Bert et al., KDD 2023: 4068-4077. doi:10.1145/3580305.3599933\n\n## Contact\n\nYou can contact the core development team at\n[decision-forests-contact@google.com](mailto:decision-forests-contact@google.com).\n\n## Credits\n\nTensorFlow Decision Forests was developed by:\n\n-   Mathieu Guillame-Bert (gbm AT google DOT com)\n-   Jan Pfeifer (janpf AT google DOT com)\n-   Richard Stotz (richardstotz AT google DOT com)\n-   Sebastian Bruch (sebastian AT bruch DOT io)\n-   Arvind Srinivasan (arvnd AT google DOT com)\n\n## License\n\n[Apache License 2.0](LICENSE)\n","funding_links":[],"categories":["Python","Machine Learning","梯度提升和树模型"],"sub_categories":["Gradient Boosting"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorflow%2Fdecision-forests","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftensorflow%2Fdecision-forests","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorflow%2Fdecision-forests/lists"}