一般化
一致性(知识库)
统计理论
机器学习
计算机科学
多样性(控制论)
过程(计算)
算法学习理论
统计学习理论
学习理论
功能(生物学)
人工智能
数学
无监督学习
统计
数学教育
数学分析
进化生物学
支持向量机
生物
操作系统
作者
Yuhai Wu,Vladimir Vapnik
出处
期刊:Technometrics
[Informa]
日期:1999-11-01
卷期号:41 (4): 377-377
被引量:6720
摘要
A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
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