{"id":23413158,"url":"https://github.com/zillow/quantile-forest","last_synced_at":"2025-04-05T11:12:10.532Z","repository":{"id":61533989,"uuid":"472997315","full_name":"zillow/quantile-forest","owner":"zillow","description":"Quantile Regression Forests compatible with scikit-learn.","archived":false,"fork":false,"pushed_at":"2024-04-11T08:22:30.000Z","size":18141,"stargazers_count":151,"open_issues_count":0,"forks_count":19,"subscribers_count":11,"default_branch":"main","last_synced_at":"2024-04-13T23:07:24.442Z","etag":null,"topics":["machine-learning","prediction-intervals","python","quantile-regression","quantile-regression-forests","random-forest","scikit-learn-api","uncertainty-estimation"],"latest_commit_sha":null,"homepage":"https://zillow.github.io/quantile-forest/","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/zillow.png","metadata":{"files":{"readme":"README.md","changelog":null,"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":"AUTHORS","dei":null}},"created_at":"2022-03-23T01:33:57.000Z","updated_at":"2024-04-15T13:42:58.566Z","dependencies_parsed_at":"2022-10-20T10:15:34.519Z","dependency_job_id":"65ba9ae9-1949-4ee7-9e76-bd71443f12ab","html_url":"https://github.com/zillow/quantile-forest","commit_stats":null,"previous_names":[],"tags_count":18,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zillow%2Fquantile-forest","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zillow%2Fquantile-forest/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zillow%2Fquantile-forest/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zillow%2Fquantile-forest/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zillow","download_url":"https://codeload.github.com/zillow/quantile-forest/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247325693,"owners_count":20920714,"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":["machine-learning","prediction-intervals","python","quantile-regression","quantile-regression-forests","random-forest","scikit-learn-api","uncertainty-estimation"],"created_at":"2024-12-22T19:25:33.524Z","updated_at":"2025-04-05T11:12:05.522Z","avatar_url":"https://github.com/zillow.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# quantile-forest \u003ca href=\"https://zillow.github.io/quantile-forest/\"\u003e\u003cimg align=\"right\" src=\"https://zillow.github.io/quantile-forest/_static/quantile-forest-logo.png\" height=\"50\"\u003e\u003c/img\u003e\u003c/a\u003e\n\n[![PyPI - Version](https://img.shields.io/pypi/v/quantile-forest)](https://pypi.org/project/quantile-forest)\n[![License](https://img.shields.io/github/license/zillow/quantile-forest)](https://github.com/zillow/quantile-forest/blob/main/LICENSE)\n[![GitHub Actions](https://github.com/zillow/quantile-forest/actions/workflows/build.yml/badge.svg)](https://github.com/zillow/quantile-forest/actions/workflows/build.yml)\n[![Codecov](https://codecov.io/gh/zillow/quantile-forest/branch/main/graph/badge.svg?token=STRT8T67YP)](https://codecov.io/gh/zillow/quantile-forest)\n[![Code Style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![DOI](https://joss.theoj.org/papers/10.21105/joss.05976/status.svg)](https://doi.org/10.21105/joss.05976)\n\n**quantile-forest** offers a Python implementation of quantile regression forests compatible with scikit-learn.\n\nQuantile regression forests (QRF) are a non-parametric, tree-based ensemble method for estimating conditional quantiles, with application to high-dimensional data and uncertainty estimation [[1]](#1). The estimators in this package are performant, Cython-optimized QRF implementations that extend the forest estimators available in scikit-learn to estimate conditional quantiles. The estimators can estimate arbitrary quantiles at prediction time without retraining and provide methods for out-of-bag estimation, calculating quantile ranks, and computing proximity counts. They are compatible with and can serve as drop-in replacements for the scikit-learn forest regressors.\n\n#### Example of fitted model predictions and prediction intervals on California housing data ([code](https://zillow.github.io/quantile-forest/gallery/plot_qrf_prediction_intervals.html))\n\u003cimg src=\"https://zillow.github.io/quantile-forest/_static/plot_qrf_prediction_intervals.png\"/\u003e\n\nQuick Start\n-----------\n\nTo install quantile-forest from [PyPI](https://pypi.org/project/quantile-forest) using `pip`:\n\n```bash\npip install quantile-forest\n```\n\nTo install quantile-forest from [conda-forge](https://anaconda.org/conda-forge/quantile-forest) using `conda`:\n\n```bash\nconda install quantile-forest -c conda-forge\n```\n\nUsage\n-----\n\n```python\nfrom quantile_forest import RandomForestQuantileRegressor\nfrom sklearn import datasets\nX, y = datasets.fetch_california_housing(return_X_y=True)\nqrf = RandomForestQuantileRegressor()\nqrf.fit(X, y)\ny_pred = qrf.predict(X, quantiles=[0.025, 0.5, 0.975])\n```\n\nDocumentation\n-------------\n\nAn installation guide, API documentation, and examples can be found in the [documentation](https://zillow.github.io/quantile-forest).\n\n\nReferences\n----------\n\n\u003ca id=\"1\"\u003e[1]\u003c/a\u003e N. Meinshausen, \"Quantile Regression Forests\", Journal of Machine Learning Research, 7(Jun), 983-999, 2006. http://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf\n\nCitation\n--------\n\nIf you use this package in academic work, please consider citing https://joss.theoj.org/papers/10.21105/joss.05976:\n\n```bib\n@article{Johnson2024,\n    doi = {10.21105/joss.05976},\n    url = {https://doi.org/10.21105/joss.05976},\n    year = {2024},\n    publisher = {The Open Journal},\n    volume = {9},\n    number = {93},\n    pages = {5976},\n    author = {Reid A. Johnson},\n    title = {quantile-forest: A Python Package for Quantile Regression Forests},\n    journal = {Journal of Open Source Software}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzillow%2Fquantile-forest","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzillow%2Fquantile-forest","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzillow%2Fquantile-forest/lists"}