{"id":14066672,"url":"https://github.com/VaishaliJain/ethnicIA","last_synced_at":"2025-07-29T23:32:00.120Z","repository":{"id":92211948,"uuid":"501357471","full_name":"VaishaliJain/ethnicIA","owner":"VaishaliJain","description":"\"The Importance of being Ernest, Ekundayo, or Eswari: An Interpretable Machine Learning Approach to Name-based Ethnicity Classification\" Authors: Vaishali Jain, Ted Enamorado, and Cynthia Rudin","archived":false,"fork":false,"pushed_at":"2023-01-06T18:06:50.000Z","size":21287,"stargazers_count":6,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"main","last_synced_at":"2024-12-04T06:36:42.227Z","etag":null,"topics":["interpretability","interpretable-machine-learning","name-classification"],"latest_commit_sha":null,"homepage":"https://hdsr.mitpress.mit.edu/pub/wgss79vu/release/2","language":"R","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/VaishaliJain.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":"2022-06-08T17:57:26.000Z","updated_at":"2024-10-28T05:47:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"fc5f4f7d-3cca-4e00-8686-fa8878187351","html_url":"https://github.com/VaishaliJain/ethnicIA","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/VaishaliJain/ethnicIA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VaishaliJain%2FethnicIA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VaishaliJain%2FethnicIA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VaishaliJain%2FethnicIA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VaishaliJain%2FethnicIA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/VaishaliJain","download_url":"https://codeload.github.com/VaishaliJain/ethnicIA/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VaishaliJain%2FethnicIA/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":267780010,"owners_count":24143201,"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":"2025-07-29T02:00:12.549Z","response_time":2574,"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":["interpretability","interpretable-machine-learning","name-classification"],"created_at":"2024-08-13T07:05:12.700Z","updated_at":"2025-07-29T23:31:58.398Z","avatar_url":"https://github.com/VaishaliJain.png","language":"R","funding_links":[],"categories":["R"],"sub_categories":[],"readme":"# ethnicIA\n\n![](/Images/ethnicIA_logo.png?raw=true)\n\n\"The Importance of being Ernest, Ekundayo, or Eswari: An Interpretable Machine Learning Approach to Name-based Ethnicity Classification\"\nAuthors: Vaishali Jain, Ted Enamorado, and Cynthia Rudin\n\nCitation: Jain, V., Enamorado, T., \u0026 Rudin, C. (2022). The Importance of Being Ernest, Ekundayo, or Eswari: An Interpretable Machine Learning Approach to Name-Based Ethnicity Classification. Harvard Data Science Review, 4(3). https://doi.org/10.1162/99608f92.db1aba8b\n\n# Data\n\nYou can download the datasets from NC and FL from here: https://users.cs.duke.edu/~cynthia/ethnicIA/Data/. The GA data is not publicly available, so we have created 3 processed training and test datasets using only NC and FL that can be useful for testing algorithms.\n\n# Steps to replicate experiments, case study, and appendices\n\nStep 1: Run Code/R/01_Create_Train_Features_Master_sparse.R and Code/R/01_Create_Train_Features_Master_UID.R to generate all training datasets\nStep 2: Run Code/R/02_Create_Test_Features_Master_sparse.R and Code/R/02_Create_Test_Features_Master_UID.R to generate all test datasets\nStep 3: Run function ethnicIA_model_training() in Code/python/ethnicIA_paper_results.py file to train all the required models\nStep 4: Run functions corresponding to the respective experiment from Code/python/ethnicIA_paper_results.py file to replicate the results.\n\nFollow any instruction provided in the functions in the python file. \n(Open up Code/python/ethnicIA_paper_results.py for clarification on this step.)\n\n# Replication for Section 3: Sensitivity of parameters for Indistinguishibility\n\nRun Code/R/03_Create_Features_FLGA_multCuts.R and Code/R/03_Plot_multCuts.R to generate the contour plot shown in Figure 1.\n\n![Namespace](/Images/Namespace.png?raw=true \"Namespace\")\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FVaishaliJain%2FethnicIA","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FVaishaliJain%2FethnicIA","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FVaishaliJain%2FethnicIA/lists"}