控制成本:在预算中选择功能
Guo Yu1, Daniela Witten2, Jacob Bien3
1Department of Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, California, USA.
概括
这项研究引入了"廉价仿制品",一种成本意识的功能选择方法. 它确保昂贵的特征得到更多的审查,最大限度地减少浪费的研究成本,并在预算限制范围内优化模型的准确性.
科学领域:
- 机器学习 机器学习
- 统计建模 统计建模
- 生物信息学是一种生物信息学.
背景情况:
- 传统的特征选择假设统一的特征成本,忽视现实世界资源限制.
- 可变的测量成本 (金融,时间等) 以模型准确性呈现一个关键的权衡.
- 不必要地包含高成本的功能会对研究效率和预算产生不成比例的影响.
研究的目的:
- 开发一个具有成本意识的功能选择程序.
- 引入一种能够考虑可变测量成本的方法.
- 为在预算限制下优化特征选择提供框架.
主要方法:
- 提出了一种名为"廉价仿制"的新程序,用于成本意识的功能选择.
- 核心创新涉及增加竞争 (淘汰) 的更高成本的功能.
- 在与特征成本相关的加权错误发现比例上推导出理论上限.
主要成果:
- "廉价仿制"程序限制了浪费的功能成本分数.
- 导出边界在一系列特征集大小中同时具有很高的概率.
- 模拟和生物医学应用证明了成本意识选择的实际好处.
结论:
- "廉价仿制"方法使得预算驱动的功能选择成为可能.
- 用户可以选择具有浪费成本保证上限的功能集.
- 纳入成本考虑因素显著提高了功能选择过程的效率.
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