A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书


A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)

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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书 著者简介


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发表于2024-05-21

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书



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出版者:Springer
作者:Luc Devroye
出品人:
页数:651
译者:
出版时间:1996-04-04
价格:USD 109.00
装帧:Hardcover
isbn号码:9780387946184
丛书系列:

图书标签: 机器学习  模式识别  pattern_recognition  Statistics  概率论与统计学  统计学习  统计  计算机技术   


A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书 图书描述

A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书
想要找书就要到 本本书屋
立刻按 ctrl+D收藏本页
你会得到大惊喜!!

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 用户评价

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Another rigorous textbook on learning theory. Focus on the nonparametric methods. Highly recommended!

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从nonparametric statistics的角度研究机器学习算法,主要关注点是算法的consistency(是否能渐进逼近Bayes error),主要使用的工具是几个中心不等式(尤其是Vapnik-Chervonenkis不等式),分析的算法包括最近邻、histogram、决策树等。书中有不少脑洞很大的证明,刚开始看还是挺吃力的。习题都很难,还没有答案。唯一的缺憾是太老了,毕竟是二十年前出版的。

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这本书可以cite到很多folklore,基础理论值得反复重读。minimax部分非常系统。

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从nonparametric statistics的角度研究机器学习算法,主要关注点是算法的consistency(是否能渐进逼近Bayes error),主要使用的工具是几个中心不等式(尤其是Vapnik-Chervonenkis不等式),分析的算法包括最近邻、histogram、决策树等。书中有不少脑洞很大的证明,刚开始看还是挺吃力的。习题都很难,还没有答案。唯一的缺憾是太老了,毕竟是二十年前出版的。

评分

Another rigorous textbook on learning theory. Focus on the nonparametric methods. Highly recommended!

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) 2024 pdf epub mobi 电子书


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