{"id":19578553,"url":"https://github.com/materialsproject/gbml","last_synced_at":"2025-08-31T16:39:29.125Z","repository":{"id":57433180,"uuid":"53978825","full_name":"materialsproject/gbml","owner":"materialsproject","description":"Gradient Boosting Machine-Locfit: A GBM framework using local regresssion via Locfit.","archived":false,"fork":false,"pushed_at":"2021-05-12T20:05:53.000Z","size":2838,"stargazers_count":6,"open_issues_count":4,"forks_count":6,"subscribers_count":12,"default_branch":"master","last_synced_at":"2025-04-25T09:17:19.313Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"http://ect.bell-labs.com/sl/project/locfit/index.html","language":"C","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/materialsproject.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}},"created_at":"2016-03-15T21:11:51.000Z","updated_at":"2024-07-20T23:41:00.000Z","dependencies_parsed_at":"2022-08-27T20:52:09.331Z","dependency_job_id":null,"html_url":"https://github.com/materialsproject/gbml","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/materialsproject%2Fgbml","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/materialsproject%2Fgbml/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/materialsproject%2Fgbml/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/materialsproject%2Fgbml/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/materialsproject","download_url":"https://codeload.github.com/materialsproject/gbml/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251099351,"owners_count":21536146,"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":"2024-11-11T07:11:54.563Z","updated_at":"2025-04-27T06:33:45.850Z","avatar_url":"https://github.com/materialsproject.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"Gradient Boosting Machine-Locfit: A GBM framework using local regresssion via Locfit.\nFor information on Locfit see: http://ect.bell-labs.com/sl/project/locfit/index.html\n\nThis package offers predictions for bulk and shear moduli given material descriptors and training data.\n\n### Citing\nde Jong M, Chen W, Notestine R, Persson K, Ceder G, Jain A, Asta M, Gamst A. \"A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds.\" *Scientific Reports* **6**: 34256 (2016) | [doi:10.1038/srep34256](http://dx.doi.org/10.1038/srep34256).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmaterialsproject%2Fgbml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmaterialsproject%2Fgbml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmaterialsproject%2Fgbml/lists"}