{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/diagonal-discriminant-analysis-with-feature","title":"Diagonal Discriminant Analysis with Feature Selection for High Dimensional Data","arxiv_id":"1807.01422","date":"2018-07-04","proceeding":null,"authors":["Sarah Elizabeth Romanes","John Thomas Ormerod","Jean YH Yang"],"abstract":"We introduce a new method of performing high dimensional discriminant\nanalysis, which we call multiDA. We achieve this by constructing a hybrid model\nthat seamlessly integrates a multiclass diagonal discriminant analysis model\nand feature selection components. Our feature selection component naturally\nsimplifies to weights which are simple functions of likelihood ratio statistics\nallowing natural comparisons with traditional hypothesis testing methods. We\nprovide heuristic arguments suggesting desirable asymptotic properties of our\nalgorithm with regards to feature selection. We compare our method with several\nother approaches, showing marked improvements in regard to prediction accuracy,\ninterpretability of chosen features, and algorithm run time. We demonstrate\nsuch strengths of our model by showing strong classification performance on\npublicly available high dimensional datasets, as well as through multiple\nsimulation studies. We make an R package available implementing our approach.","url_abs":"http://arxiv.org/abs/1807.01422v1","url_pdf":"http://arxiv.org/pdf/1807.01422v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"diagonal-discriminant-analysis-with-feature","repo_url":"https://github.com/sarahromanes/multiDA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"hypothesis-testing","task_name":"Two-sample testing"},{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"},{"task_slug":"feature-selection","task_name":"feature selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}