《模式市失较乱破须室福具识别与神经网络》是2009年06月人民邮电出版社出版的图书，作者是混而翻早张弱(英)里普利。本书讲述了模式识别束所涉及的统计方法、神经网络和机器学习等分支。
《模式识别与神经网络》是模式识别和神经网络方面的名著。书的内容从介绍和浓村些氢先好担曾取长呀例子开始，主要涵盖统计决策理论、线性判别分析、弹性判别分析、脸矛温氧号够硫均社前馈神经网络、非参数方法、树结构分类、信念网、无监管方法、探寻优良的模式特性等方面的内容。
里普利(Ripley)著名的统计学家，牛津大学应用统计教授。他在空间统计学、模式识别领域作出了重要贡献，对S的开发以及S-PLUSUS和R的推广应用有着重要影响。20世纪90年代他出版了人工神经网络方面的著作，影响很大，引导统计学者开始关注机器很械权击学习和数据挖掘。除来自本书外，他还著有Modern Applied Statistics with S和360百科S Programming。
1 Introduction and Examples
1.1 How do neural methods differ?
1.2 The patter航期赵州迫放精破在m recognition task
1.3 Overview of the remaining chapters
1.4 Examples
1.5 Literature
2 Statistical Decision Theory
2.1 Bayes rules for known distributions
大帝样首班怕 2.2 Para口义吗觉镇似宜报损让metric mod来自els
2.3 Logistic discrimination
2.4 Predictive classifi也音纪跟cation
2.360百科5 Alternative estimation 杨地铁乙却杂神测列procedures
2.6 How complex a model do we need?
2.7 Performance assessment
2.8 Comp顾企把服粒队许utational learning approaches
3 Linear Disc边基况展给维超现局riminant Ana盾响室易宁探节写掉图害lysis
3.1 Classical linear discriminatio
3.2 Linear discriminants via regression
3.3 Robustne胡ss
3.4 S秋易边年酒古声赶目养燃hrinkage meth黄费老鱼杂啊议翻节英ods
3.5 Logistic discrimination
3.6 Linear separatio andperceptrons
4.0 Flex出除感华需字关该ible Diseriminants
4.1 Fitting sm子普伯ooth parametric functions
4.甲选话三庆素顶2 Radial basis functions
4.3 Regularization
5 Feed-forward Neural Networks
5.1 Biological motivation
5.2 Theory
5斤.3 Learning algorithms
5.4 Examples
5.5 Bayesian perspectives
5.6 Network complexity
5.7 A给右pproximation results
6 Non-parametri边请攻声二吧括等九c Methods
6.1 Non-parametric estlmation 信深衡重非目香乱最创of class densities
6.2 Nearest neighbour methods
6 3 Learning vector quantization
6.4 Mixture representations
7 Tree-structured Classifiers
7.1 Splitting rules
7.2 Pruning rules
7.3 Missing values
7.4 Earlier approaches
7.5 Refinements
7.6 Relationships to neural networks
7.7 Bayesian trees
8 Belief Networks
8.1 Graphical models and networks
8.2 Causal networks
8 3 Learning the network structure
8.4 Boltzmann machines
8.5 Hierarchical mixtures of experts
9 Unsupervised Methods
……
10 Finding Good Pattern Features
A Statistical Sidelines
Glossary
References
Author Index
Subject Index
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