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We also show that the\nreweighted feature selection method, which approximates the optimized feature\nmap, helps improve the performance of RFSVM in experiments on a synthetic data\nset.","url_abs":"http://arxiv.org/abs/1809.04481v3","url_pdf":"http://arxiv.org/pdf/1809.04481v3.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":"but-how-does-it-work-in-theory-linear-svm","repo_url":"https://github.com/syitong/randfourier","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"feature-selection","task_name":"feature selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1809.04481","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1809.04481"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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