{"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/orthogonal-matching-pursuit-for-text","title":"Orthogonal Matching Pursuit for Text Classification","arxiv_id":"1807.04715","date":"2018-07-12","proceeding":"WS 2018 11","authors":["Konstantinos Skianis","Nikolaos Tziortziotis","Michalis Vazirgiannis"],"abstract":"In text classification, the problem of overfitting arises due to the high\ndimensionality, making regularization essential. Although classic regularizers\nprovide sparsity, they fail to return highly accurate models. On the contrary,\nstate-of-the-art group-lasso regularizers provide better results at the expense\nof low sparsity. In this paper, we apply a greedy variable selection algorithm,\ncalled Orthogonal Matching Pursuit, for the text classification task. We also\nextend standard group OMP by introducing overlapping Group OMP to handle\noverlapping groups of features. Empirical analysis verifies that both OMP and\noverlapping GOMP constitute powerful regularizers, able to produce effective\nand very sparse models. Code and data are available online:\nhttps://github.com/y3nk0/OMP-for-Text-Classification .","url_abs":"http://arxiv.org/abs/1807.04715v2","url_pdf":"http://arxiv.org/pdf/1807.04715v2.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":"orthogonal-matching-pursuit-for-text","repo_url":"https://github.com/y3nk0/OMP-for-Text-Classification","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"text-classification","task_name":"Text Classification"},{"task_slug":"variable-selection","task_name":"Variable Selection"},{"task_slug":"text-classification-1","task_name":"text-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}