Estimation of Dependences Based on Empirical Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Vladimir Vapnik 作者

Springer

Kotz, S. 译者

2006-03-28 出版日期

524 页数

USD 69.95 价格

Hardcover

丛书系列

9780387308654 图书编码

Estimation of Dependences Based on Empirical Data 在线电子书图书标签: 机器学习 Statistics Learning 機器學習俄國人工智能 a Vladimir_Vapnik

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Estimation of Dependences Based on Empirical Data 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Estimation of Dependences Based on Empirical Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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统计学习理论背后一些故事，读来饶有兴趣。

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这本书是80年代EDBED的再版,分为2个部分,第一部分跟82年版几乎一样,第二部分是老瓦新写的,相当于<寄小读者>,讲了很多好玩的东西,江湖恩怨什么的,值得一看

评分☆☆☆☆☆

统计学习理论背后一些故事，读来饶有兴趣。

评分☆☆☆☆☆

统计学习理论背后一些故事，读来饶有兴趣。

评分☆☆☆☆☆

统计学习理论背后一些故事，读来饶有兴趣。

Estimation of Dependences Based on Empirical Data 在线电子书著者简介

Estimation of Dependences Based on Empirical Data 在线电子书图书目录

Estimation of Dependences Based on Empirical Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Estimation of Dependences Based on Empirical Data 在线电子书图书描述

In 1982, Springer published the English translation of the Russian book Estimation of Dependencies Based on Empirical Data which became the foundation of the statistical theory of learning and generalization (the VC theory). A number of new principles and new technologies of learning, including SVM technology, have been developed based on this theory. The second edition of this book contains two parts: - A reprint of the first edition which provides the classical foundation of Statistical Learning Theory - Four new chapters describing the latest ideas in the development of statistical inference methods. They form the second part of the book entitled Empirical Inference Science The second part of the book discusses along with new models of inference the general philosophical principles of making inferences from observations. It includes new paradigms of inference that use non-inductive methods appropriate for a complex world, in contrast to inductive methods of inference developed in the classical philosophy of science for a simple world. The two parts of the book cover a wide spectrum of ideas related to the essence of intelligence: from the rigorous statistical foundation of learning models to broad philosophical imperatives for generalization. The book is intended for researchers who deal with a variety of problems in empirical inference: statisticians, mathematicians, physicists, computer scientists, and philosophers.

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