{"id":20837757,"url":"https://github.com/astrazeneca/dpp_imp","last_synced_at":"2026-04-20T22:07:16.464Z","repository":{"id":207181641,"uuid":"718099494","full_name":"AstraZeneca/dpp_imp","owner":"AstraZeneca","description":"Improved clinical data imputation via classical and quantum determinantal point processes","archived":false,"fork":false,"pushed_at":"2024-04-03T21:20:50.000Z","size":16,"stargazers_count":1,"open_issues_count":1,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-18T23:00:04.074Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AstraZeneca.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-11-13T11:31:10.000Z","updated_at":"2023-11-14T12:25:33.000Z","dependencies_parsed_at":"2023-11-14T14:45:07.105Z","dependency_job_id":null,"html_url":"https://github.com/AstraZeneca/dpp_imp","commit_stats":null,"previous_names":["astrazeneca/dpp_imp"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fdpp_imp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fdpp_imp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fdpp_imp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fdpp_imp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AstraZeneca","download_url":"https://codeload.github.com/AstraZeneca/dpp_imp/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243195960,"owners_count":20251845,"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":"2024-11-18T01:08:30.745Z","updated_at":"2025-12-26T22:58:25.850Z","avatar_url":"https://github.com/AstraZeneca.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data imputation using Determinantal Point Process (DPP) - based methods\n\nPlease contact [Philip Teare](mailto:philip.teare@astrazeneca.com) with any questions about this repo. \n\nThis work presents an implementation of the models presented in the \"[Improved clinical data imputation via classical and quantum determinantal point processes](https://arxiv.org/abs/2303.17893)\" paper\n\n## Prerequisites\n\nPython 3.9\n\n## Usage\n\n```python\n\nfrom models.imputers import DPPMissForest\n\nddpp_mf = DPPMissForest(batch_size=100, max_iter=5, n_estimators=10)\n\nX_imputed = ddpp_mf.fit_transform(X_missing)\n\n```\n\n## License\n\n[MIT](https://choosealicense.com/licenses/mit/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fastrazeneca%2Fdpp_imp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fastrazeneca%2Fdpp_imp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fastrazeneca%2Fdpp_imp/lists"}