{"id":20807048,"url":"https://github.com/doubleml/dml-hyperparameter-tuning-replication","last_synced_at":"2025-09-07T03:38:16.622Z","repository":{"id":217881862,"uuid":"745025312","full_name":"DoubleML/DML-Hyperparameter-Tuning-Replication","owner":"DoubleML","description":"In this Repo we provide the replication code to our simulations as well as the results.","archived":false,"fork":false,"pushed_at":"2024-01-29T21:54:57.000Z","size":22658,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-27T03:54:19.997Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/DoubleML.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-01-18T13:49:09.000Z","updated_at":"2024-09-23T20:31:57.000Z","dependencies_parsed_at":"2024-11-17T19:43:02.829Z","dependency_job_id":null,"html_url":"https://github.com/DoubleML/DML-Hyperparameter-Tuning-Replication","commit_stats":null,"previous_names":["oliverschacht/dml-hyperparameter-tuning-replication"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/DoubleML/DML-Hyperparameter-Tuning-Replication","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DoubleML%2FDML-Hyperparameter-Tuning-Replication","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DoubleML%2FDML-Hyperparameter-Tuning-Replication/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DoubleML%2FDML-Hyperparameter-Tuning-Replication/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DoubleML%2FDML-Hyperparameter-Tuning-Replication/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DoubleML","download_url":"https://codeload.github.com/DoubleML/DML-Hyperparameter-Tuning-Replication/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DoubleML%2FDML-Hyperparameter-Tuning-Replication/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273993043,"owners_count":25203792,"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","status":"online","status_checked_at":"2025-09-07T02:00:09.463Z","response_time":67,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":"2024-11-17T19:30:16.499Z","updated_at":"2025-09-07T03:38:16.590Z","avatar_url":"https://github.com/DoubleML.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DML Hyperparameter Tuning Replication Files\nIn this Repo we provide the replication code to our simulations as well as the results. The code for the motivating example (Section 2) is provided in the subdirectory `motivation_example_BCH`, see [the separate README file](motivation_example_BCH/README.md) for more information.\n\n## Data Generating Processes\nThe data generating processes (dgp) can be found in the `dgp` folder. Note: Due to capacity constrains, we do not provide the `ACIC` datasets. However, the `R` files creating the datasets can be found on the [ACIC 2019 data challenge website]([https://drive.google.com/file/d/1Qqgmb3R9Vt9KTx6t8i_5IbFenylsPfrK/view?usp=sharing](https://sites.google.com/view/acic2019datachallenge/data-challenge)https://sites.google.com/view/acic2019datachallenge/data-challenge).\n\n## Simulation Files\nThe files for running the simulation study can be found in the `simulations` folder.\n\n## Results\nThe text files containing the raw results of our simulation runs can be found in the `results` folder.\n\n## Figures and Tables\nThe notebooks creating the figures and tables from the paper can be found int the `evaluation` folder.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdoubleml%2Fdml-hyperparameter-tuning-replication","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdoubleml%2Fdml-hyperparameter-tuning-replication","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdoubleml%2Fdml-hyperparameter-tuning-replication/lists"}