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한국어(KO) fly51fly (@fly51fly) Michigan과 Google Research 연구진이 구조화 데이터에 대해 진화적 특성 공학을 수행하는 방법을 제안했습니다. 전통적 ML 파이프라인의 피처 엔지니어링 자동화 관점에서 흥미로운 연구입니다. https:// x.com/fly51fly/

密歇根大学和 Google Research 探索演化特征工程

密歇根大学和 Google Research 的研究人员提出了一种对结构化数据进行演化特征工程的方法。这项工作因其在自动化传统机器学习管道中的特征工程方面的潜力而备受关注。 AI

排序理由 该集群描述了一项关于机器学习特征工程的研究提案。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — sigmoid.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

密歇根大学和 Google Research 探索演化特征工程

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该集群描述了一项关于机器学习特征工程的研究提案。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Mastodon — sigmoid.social TIER_1 한국어(KO) · [email protected] ·

    fly51fly (@fly51fly) 提出了一种基于密歇根大学和 Google Research 研究人员的结构化数据演化特征工程方法。从传统机器学习管道中自动化特征工程的角度来看,这是一项有趣的研究。https:// x.com/fly51fly/

    fly51fly (@fly51fly) Michigan과 Google Research 연구진이 구조화 데이터에 대해 진화적 특성 공학을 수행하는 방법을 제안했습니다. 전통적 ML 파이프라인의 피처 엔지니어링 자동화 관점에서 흥미로운 연구입니다. https:// x.com/fly51fly/status/20731557 26814609469 # featureengineering # structureddata # ml # research # google