{"id":6200,"date":"2025-02-10T05:03:00","date_gmt":"2025-02-09T20:03:00","guid":{"rendered":"https:\/\/devneko.jp\/wordpress\/?p=6200"},"modified":"2025-02-10T05:03:00","modified_gmt":"2025-02-09T20:03:00","slug":"transformers-boost-the-performance-of-decision-trees-on-tabular-data-across-sample-sizes","status":"publish","type":"post","link":"https:\/\/devneko.jp\/wordpress\/?p=6200","title":{"rendered":"Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes\u00a0"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li><strong>Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes\u00a0<\/strong>[135.7]<br>\u672c\u7a3f\u3067\u306f,\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u3068\u52fe\u914d\u30d6\u30fc\u30b9\u30c8\u6c7a\u5b9a\u6728\u3092\u878d\u5408\u3055\u305b\u308b,\u30b7\u30f3\u30d7\u30eb\u3067\u8efd\u91cf\u306a\u624b\u6cd5\u3092\u63d0\u6848\u3059\u308b\u3002 \u878d\u5408\u6cd5\u3092 LLM-Boost \u3068 PFN-Boost \u3068\u547d\u540d\u3057\u305f\u3002 \u591a\u6570\u306e\u30d9\u30fc\u30b9\u30e9\u30a4\u30f3\u3068\u30a2\u30f3\u30b5\u30f3\u30d6\u30eb\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306b\u5bfe\u3057\u3066\u6700\u5148\u7aef\u306e\u6027\u80fd\u3092\u793a\u3059\u3002<br><a href=\"http:\/\/arxiv.org\/abs\/2502.02672v2\">\u8ad6\u6587<\/a>\u00a0\u00a0<a href=\"https:\/\/fugumt.com\/fugumt\/paper_check\/2502.02672v2\">\u53c2\u8003\u8a33\uff08\u30e1\u30bf\u30c7\u30fc\u30bf\uff09<\/a>\u00a0 \u00a0(Thu, 06 Feb 2025 02:39:35 GMT)<\/li>\n\n\n\n<li>\u300cWe propose LLM-Boost: a novel yet simple and easy-to-implement boosting mechanism that combines LLMs, which ingest semantic column headers, with GBDTs that can scale to massive datasets.\u300d\u3001\u300cWe further propose PFN-Boost, where we instead fuse TabPFN and GBDTs for performance gains over GBDTs alone across dataset sizes without using column headers.\u300d\u3068LLM\u3084Transformer\u3068GBDT\u3092\u878d\u5408\u3059\u308b\u30a2\u30d7\u30ed\u30fc\u30c1\u3002\u30c7\u30fc\u30bf\u30b5\u30a4\u30ba\u306b\u3088\u3063\u3066\u52b9\u679c\u304c\u3042\u308b\u3068\u3044\u3046\u306e\u306f\u305d\u3046\u3060\u308d\u3046\u3068\u601d\u3046\u3002<\/li>\n\n\n\n<li>\u30ea\u30dd\u30b8\u30c8\u30ea\u306f<a href=\"https:\/\/github.com\/MayukaJ\/LLM-Boost\">GitHub &#8211; MayukaJ\/LLM-Boost<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[223,453,498],"class_list":["post-6200","post","type-post","status-publish","format-standard","hentry","category-arxiv","tag-llm","tag-xgboost","tag-498"],"_links":{"self":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/6200","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6200"}],"version-history":[{"count":0,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/6200\/revisions"}],"wp:attachment":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6200"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6200"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6200"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}