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Statistical Learning Theory读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 768页 9.5 2020 Wiley-Interscience
定价 出版日期 最近访问 访问指数
USD 221.00 2020-02-20 … 2020-03-07 … 43
主题/类型/题材/标签
统计学习,机器学习,Statistics,MachineLearning,数学,Vapnik,统计学,Theory,
作者
Vladimir N. Vapnik      ISBN:9780471030034    原作名/别名:《》
内容和作者简介
Statistical Learning Theory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...

作者简介

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.

本书后续版本
未发行或暂未收录
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