《模式识别与机器学习》 - Christopher Bishop详细介绍了模式识别和机器学习的基础理论和技术 15.91MB

xianyinsuifeng

资源文件列表:

Bishop-Pattern-Recognition-and-Machine-Learning-2006.zip 大约有1个文件

Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf 17.25MB

资源介绍:

《模式识别与机器学习》（Pattern Recognition and Machine Learning）是Christopher M. Bishop所著的一本经典教材，详细介绍了模式识别和机器学习领域的基本理论和方法。以下是对该书的具体介绍：内容简介《模式识别与机器学习》系统地介绍了模式识别和机器学习的基本概念、理论和方法，覆盖了从概率分布、贝叶斯方法，到图模型、神经网络等一系列主题。该书以统计学习理论为基础，详细讨论了各种算法和模型，并通过大量的实例和习题帮助读者理解和应用这些方法。章节概述机器学习和模式识别的基本概念和应用领域。概率论基础，概率分布及其在模式识别中的应用。线性回归、线性分类器、支持向量机（SVM）等线性模型。 Fisher判别分析、多类别分类器。感知机、多层前馈神经网络、反向传播算法。支持向量机、核函数、核技巧。贝叶斯网络、马尔可夫随机场、推理和学习。混合模型和EM算法高斯混合模型、期望最大化（EM）算法。变分推断、MCMC方法。马尔可夫链蒙特卡罗（MCMC）、Gibbs采样。主成分分析（PCA）、因子分析、独立成分分析（ICA）。

<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89603925/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89603925/bg1.jpg"/></div><div class="pi" data-data='{"ctm":[1.902459,0.000000,0.000000,1.902459,0.000000,0.000000]}'></div></div><div id="pf2" class="pf w2 h2" data-page-no="2"><div class="pc pc2 w2 h2"><img class="bi x0 y0 w3 h3" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89603925/bg2.jpg"><div class="t m0 x1 h4 y1 ff1 fs0 fc0 sc0 ls0 ws0">Information<span class="_ _0"> </span>Science<span class="_ _0"> </span>and<span class="_ _0"> </span>Statistics</div><div class="t m0 x1 h5 y2 ff2 fs1 fc0 sc0 ls0 ws0">Series<span class="_ _1"> </span>Editors:</div><div class="t m0 x1 h6 y3 ff1 fs1 fc0 sc0 ls0 ws0">M.<span class="_ _1"> </span>Jordan</div><div class="t m0 x1 h6 y4 ff1 fs1 fc0 sc0 ls0 ws0">J.<span class="_ _1"> </span>Kleinberg</div><div class="t m0 x1 h6 y5 ff1 fs1 fc0 sc0 ls0 ws0">B.<span class="_ _1"> </span>Scho</div><div class="t m0 x2 h6 y6 ff1 fs1 fc0 sc0 ls0 ws0">¨</div><div class="t m0 x3 h6 y5 ff1 fs1 fc0 sc0 ls0 ws0">lkopf</div></div><div class="pi" data-data='{"ctm":[1.902459,0.000000,0.000000,1.902459,0.000000,0.000000]}'></div></div><div id="pf3" class="pf w2 h2" data-page-no="3"><div class="pc pc3 w2 h2"><img class="bi x0 y0 w3 h3" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89603925/bg3.jpg"><div class="t m1 x4 h7 y7 ff3 fs2 fc0 sc0 ls1 ws1">Information Science and Statistics </div><div class="t m1 x4 h8 y8 ff4 fs3 fc0 sc0 ls2 ws2">Akaike and Kitagawa: <span class="ff3 ls3 ws3">The Practice of Time Series Analysis. </span></div><div class="t m1 x4 h8 y9 ff4 fs3 fc0 sc0 ls4 ws0">Bishop:<span class="ff3 ls5 ws4"> Pattern Recognition and Machine Learning. </span></div><div class="t m1 x4 h8 ya ff4 fs3 fc0 sc0 ls6 ws5">Cowell, Dawid, Lauritzen, and Spiegelhalter:<span class="ff3 ws6"> Probabilistic Networks and</span></div><div class="t m1 x5 h9 yb ff3 fs3 fc0 sc0 ls7 ws7">Expert Systems. </div><div class="t m1 x4 h8 yc ff4 fs3 fc0 sc0 ls2 ws2">Doucet, de Freitas, and Gordon:<span class="ff3 ls8 ws6"> Sequential Monte Carlo Methods in Practice. </span></div><div class="t m1 x4 h8 yd ff4 fs3 fc0 sc0 ls9 ws0">Fine:<span class="ff3 ls2 ws2"> Feedforward Neural Network Methodology. </span></div><div class="t m1 x4 h8 ye ff4 fs3 fc0 sc0 ls7 ws7">Hawkins and Olwell: <span class="ff3 ls8 ws6">Cumulative Sum Charts and Charting for Quality Improvement. </span></div><div class="t m1 x4 h8 yf ff4 fs3 fc0 sc0 ls2 ws0">Jensen:<span class="_"> </span><span class="ff3 lsa ws8">Bayesian Networks and Decision Graphs. </span></div><div class="t m1 x4 h8 y10 ff4 fs3 fc0 sc0 lsb ws0">Marchette:<span class="ff3 lsc ws9"> Computer Intrusion Detection and Network Monitoring:</span></div><div class="t m1 x5 h9 y11 ff3 fs3 fc0 sc0 lsd wsa">A Statistical Viewpoint. </div><div class="t m1 x4 h8 y12 ff4 fs3 fc0 sc0 lsc ws9">Rubinstein and Kroese:<span class="_ _2"> </span><span class="ff3 lsd wsb">The Cross-Entropy Method: A Unified Approach to </span></div><div class="t m1 x5 h9 y13 ff3 fs3 fc0 sc0 lsd wsb">Combinatorial Optimization, Monte Carlo Simulation, and Machine Learning. </div><div class="t m1 x4 h8 y14 ff4 fs3 fc0 sc0 lsd ws0">Studený:<span class="ff3 wsb"> Probabilistic Conditional Independence Structures</span><span class="ff5 ls0">.</span></div><div class="t m1 x4 h8 y15 ff4 fs3 fc0 sc0 ls3 ws0">Vapnik:<span class="ff3 wsc"> The Nature of Statistical Learning Theory, Second Edition. </span></div><div class="t m1 x4 h8 y16 ff4 fs3 fc0 sc0 lse ws0">Wallace:<span class="ff3 ls8 ws6"> Statistical and Inductive Inference by Minimum Massage Length. </span></div></div><div class="pi" data-data='{"ctm":[1.902459,0.000000,0.000000,1.902459,0.000000,0.000000]}'></div></div><div id="pf4" class="pf w2 h2" data-page-no="4"><div class="pc pc4 w2 h2"><img class="bi x0 y0 w3 h3" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89603925/bg4.jpg"><div class="t m0 x1 ha y17 ff1 fs4 fc0 sc0 ls0 ws0">Christopher<span class="_ _3"> </span>M.<span class="_ _3"> </span>Bishop</div><div class="t m0 x1 hb y18 ff1 fs5 fc0 sc0 ls0 ws0">Pattern<span class="_ _4"> </span>Recognition<span class="_ _4"> </span>and</div><div class="t m0 x1 hb y19 ff1 fs5 fc0 sc0 ls0 ws0">Machine<span class="_ _4"> </span>Learning</div></div><div class="pi" data-data='{"ctm":[1.902459,0.000000,0.000000,1.902459,0.000000,0.000000]}'></div></div><div id="pf5" class="pf w2 h2" data-page-no="5"><div class="pc pc5 w2 h2"><img class="bi x0 y0 w3 h3" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89603925/bg5.jpg"><div class="t m2 x6 hc y1a ff1 fs6 fc0 sc0 ls0 ws0">Christopher<span class="_ _5"> </span>M.<span class="_ _5"> </span>Bishop<span class="_ _5"> </span>F.R.Eng.</div><div class="t m2 x6 hc y1b ff1 fs6 fc0 sc0 ls0 ws0">Assistant<span class="_ _5"> </span>Director</div><div class="t m2 x6 hc y1c ff1 fs6 fc0 sc0 ls0 ws0">Microsoft<span class="_ _5"> </span>Research<span class="_ _5"> </span>Ltd</div><div class="t m2 x6 hc y1d ff1 fs6 fc0 sc0 ls0 ws0">Cambridge<span class="_ _5"> </span>CB3<span class="_ _5"> </span>0FB,<span class="_ _5"> </span>U.K.</div><div class="t m2 x6 hc y1e ff1 fs6 fc0 sc0 ls0 ws0">cmbishop@microsoft.com</div><div class="t m2 x6 hc y1f ff1 fs6 fc0 sc0 ls0 ws0">http://research.microsoft.com/<span class="ff6">⬃</span>cmbishop</div><div class="t m2 x6 hd y20 ff2 fs6 fc0 sc0 ls0 ws0">Series<span class="_ _5"> </span>Editors</div><div class="t m2 x6 hc y21 ff1 fs6 fc0 sc0 ls0 ws0">Michael<span class="_ _5"> </span>Jordan</div><div class="t m2 x6 hc y22 ff1 fs6 fc0 sc0 ls0 ws0">Department<span class="_ _5"> </span>of<span class="_ _5"> </span>Computer</div><div class="t m2 x7 hc y23 ff1 fs6 fc0 sc0 ls0 ws0">Science<span class="_ _5"> </span>and<span class="_ _5"> </span>Department</div><div class="t m2 x7 hc y24 ff1 fs6 fc0 sc0 ls0 ws0">of<span class="_ _5"> </span>Statistics</div><div class="t m2 x6 hc y25 ff1 fs6 fc0 sc0 ls0 ws0">University<span class="_ _5"> </span>of<span class="_ _5"> </span>California,</div><div class="t m2 x7 hc y26 ff1 fs6 fc0 sc0 ls0 ws0">Berkeley</div><div class="t m2 x6 hc y27 ff1 fs6 fc0 sc0 ls0 ws0">Berkeley,<span class="_ _5"> </span>CA<span class="_ _5"> </span>94720</div><div class="t m2 x6 hc y28 ff1 fs6 fc0 sc0 ls0 ws0">USA</div><div class="t m2 x8 hc y29 ff1 fs6 fc0 sc0 ls0 ws0">Professor<span class="_ _5"> </span>Jon<span class="_ _5"> </span>Kleinberg</div><div class="t m2 x8 hc y2a ff1 fs6 fc0 sc0 ls0 ws0">Department<span class="_ _5"> </span>of<span class="_ _5"> </span>Computer</div><div class="t m2 x9 hc y2b ff1 fs6 fc0 sc0 ls0 ws0">Science</div><div class="t m2 x8 hc y2c ff1 fs6 fc0 sc0 ls0 ws0">Cornell<span class="_ _5"> </span>University</div><div class="t m2 x8 hc y2d ff1 fs6 fc0 sc0 ls0 ws0">Ithaca,<span class="_ _5"> </span>NY<span class="_ _5"> </span>14853</div><div class="t m2 x8 hc y2e ff1 fs6 fc0 sc0 ls0 ws0">USA</div><div class="t m2 xa hc y2f ff1 fs6 fc0 sc0 ls0 ws0">Bernhard<span class="_ _5"> </span>Scho</div><div class="t m2 xb hc y30 ff1 fs6 fc0 sc0 ls0 ws0">¨</div><div class="t m2 xc hc y2f ff1 fs6 fc0 sc0 ls0 ws0">lkopf</div><div class="t m2 xa hc y31 ff1 fs6 fc0 sc0 ls0 ws0">Max<span class="_ _5"> </span>Planck<span class="_ _5"> </span>Institute<span class="_ _5"> </span>for</div><div class="t m2 xd hc y32 ff1 fs6 fc0 sc0 ls0 ws0">Biological<span class="_ _5"> </span>Cybernetics</div><div class="t m2 xa hc y33 ff1 fs6 fc0 sc0 ls0 ws0">Spemannstrasse<span class="_ _5"> </span>38</div><div class="t m2 xa hc y34 ff1 fs6 fc0 sc0 ls0 ws0">72076<span class="_ _5"> </span>Tu</div><div class="t m2 xe hc y35 ff1 fs6 fc0 sc0 ls0 ws0">¨</div><div class="t m2 xf hc y34 ff1 fs6 fc0 sc0 ls0 ws0">bingen</div><div class="t m2 xa hc y36 ff1 fs6 fc0 sc0 ls0 ws0">Germany</div><div class="t m2 x6 he y37 ff1 fs7 fc0 sc0 ls0 ws0">Library<span class="_ _6"> </span>of<span class="_ _6"> </span>Congress<span class="_ _6"> </span>Control<span class="_ _6"> </span>Number:<span class="_ _6"> </span>2006922522</div><div class="t m2 x6 he y38 ff1 fs7 fc0 sc0 ls0 ws0">ISBN-10:<span class="_ _6"> </span>0-387-31073-8</div><div class="t m2 x6 he y39 ff1 fs7 fc0 sc0 ls0 ws0">ISBN-13:<span class="_ _6"> </span>978-0387-31073-2</div><div class="t m2 x6 he y3a ff1 fs7 fc0 sc0 ls0 ws0">Printed<span class="_ _6"> </span>on<span class="_ _6"> </span>acid-free<span class="_ _6"> </span>paper.</div><div class="t m2 x6 he y3b ff7 fs7 fc0 sc0 ls0 ws0">©<span class="_ _6"> </span><span class="ff1">2006<span class="_ _6"> </span>Springer<span class="_ _6"> </span>Science</span>+<span class="ff1">Business<span class="_ _6"> </span>Media,<span class="_ _6"> </span>LLC</span></div><div class="t m2 x6 he y3c ff1 fs7 fc0 sc0 ls0 ws0">All<span class="_ _6"> </span>rights<span class="_ _7"> </span>reserved.<span class="_ _6"> </span>This<span class="_ _7"> </span>work<span class="_ _6"> </span>may<span class="_ _7"> </span>not<span class="_ _6"> </span>be<span class="_ _7"> </span>translated<span class="_ _6"> </span>or<span class="_ _7"> </span>copied<span class="_ _6"> </span>in<span class="_ _7"> </span>whole<span class="_ _6"> </span>or<span class="_ _7"> </span>in<span class="_ _6"> </span>part<span class="_ _7"> </span>without<span class="_ _6"> </span>the<span class="_ _7"> </span>written<span class="_ _6"> </span>permission<span class="_ _7"> </span>of<span class="_ _6"> </span>the<span class="_ _7"> </span>publisher</div><div class="t m2 x6 he y3d ff1 fs7 fc0 sc0 ls0 ws0">(Springer<span class="_ _7"> </span>Science<span class="ff7">+</span>Business<span class="_ _7"> </span>Media,<span class="_ _6"> </span>LLC,<span class="_ _7"> </span>233<span class="_ _7"> </span>Spring<span class="_ _7"> </span>Street,<span class="_ _6"> </span>New<span class="_ _7"> </span>York,<span class="_ _7"> </span>NY<span class="_ _7"> </span>10013,<span class="_ _7"> </span>USA),<span class="_ _6"> </span>except<span class="_ _7"> </span>for<span class="_ _7"> </span>brief<span class="_ _7"> </span>excerpts<span class="_ _6"> </span>in<span class="_ _7"> </span>connection</div><div class="t m2 x6 he y3e ff1 fs7 fc0 sc0 ls0 ws0">with<span class="_ _6"> </span>reviews<span class="_ _5"> </span>or<span class="_ _5"> </span>scholarly<span class="_ _6"> </span>analysis.<span class="_ _5"> </span>Use<span class="_ _6"> </span>in<span class="_ _5"> </span>connection<span class="_ _5"> </span>with<span class="_ _6"> </span>any<span class="_ _5"> </span>form<span class="_ _5"> </span>of<span class="_ _6"> </span>information<span class="_ _5"> </span>storage<span class="_ _6"> </span>and<span class="_ _5"> </span>retrieval,<span class="_ _5"> </span>electronic<span class="_ _6"> </span>adaptation,</div><div class="t m2 x6 he y3f ff1 fs7 fc0 sc0 ls0 ws0">computer<span class="_ _6"> </span>software,<span class="_ _6"> </span>or<span class="_ _6"> </span>by<span class="_ _6"> </span>similar<span class="_ _6"> </span>or<span class="_ _6"> </span>dissimilar<span class="_ _6"> </span>methodology<span class="_ _6"> </span>now<span class="_ _6"> </span>known<span class="_ _6"> </span>or<span class="_ _6"> </span>hereafter<span class="_ _6"> </span>developed<span class="_ _6"> </span>is<span class="_ _6"> </span>forbidden.</div><div class="t m2 x6 he y40 ff1 fs7 fc0 sc0 ls0 ws0">The<span class="_ _6"> </span>use<span class="_ _6"> </span>in<span class="_ _6"> </span>this<span class="_ _6"> </span>publication<span class="_ _6"> </span>of<span class="_ _6"> </span>trade<span class="_ _6"> </span>names,<span class="_ _6"> </span>trademarks,<span class="_ _6"> </span>service<span class="_ _6"> </span>marks,<span class="_ _6"> </span>and<span class="_ _6"> </span>similar<span class="_ _5"> </span>terms,<span class="_ _6"> </span>even<span class="_ _6"> </span>if<span class="_ _6"> </span>they<span class="_ _6"> </span>are<span class="_ _6"> </span>not<span class="_ _6"> </span>identified<span class="_ _6"> </span>as<span class="_ _6"> </span>such,</div><div class="t m2 x6 he y41 ff1 fs7 fc0 sc0 ls0 ws0">is<span class="_ _6"> </span>not<span class="_ _6"> </span>to<span class="_ _6"> </span>be<span class="_ _6"> </span>taken<span class="_ _6"> </span>as<span class="_ _6"> </span>an<span class="_ _6"> </span>expression<span class="_ _6"> </span>of<span class="_ _6"> </span>opinion<span class="_ _6"> </span>as<span class="_ _6"> </span>to<span class="_ _6"> </span>whether<span class="_ _6"> </span>or<span class="_ _6"> </span>not<span class="_ _6"> </span>they<span class="_ _6"> </span>are<span class="_ _6"> </span>subject<span class="_ _6"> </span>to<span class="_ _6"> </span>proprietary<span class="_ _6"> </span>rights.</div><div class="t m2 x6 he y42 ff1 fs7 fc0 sc0 ls0 ws0">Printed<span class="_ _6"> </span>in<span class="_ _6"> </span>Singapore.<span class="_ _8"> </span>(KYO)</div><div class="t m2 x6 he y43 ff1 fs7 fc0 sc0 lsf ws0">987654321</div><div class="t m2 x6 he y44 ff1 fs7 fc0 sc0 ls0 ws0">springer.com</div></div><div class="pi" data-data='{"ctm":[1.902459,0.000000,0.000000,1.902459,0.000000,0.000000]}'></div></div>

100+评论昵称:

captcha

类型	标题	大小	时间
	Wallpaper Engine壁纸提取器 RePKG-GUI-v0.0.1.2	2.72MB	9月前

	使用delphi语言开发的计算器	1.04MB	9月前
	FatFs R0.15 FatFs源代码	9.63MB	9月前
	bugreport-Xiaomi 14 Pro-2024-08-01-104633.zip	12.97MB	9月前
	鸿蒙工具箱-HighSDK23.06	6.58MB	9月前

	魔众投票系统简单易用的投票系统	19.54MB	9月前
	linux内核学习文档	1.85MB	9月前
	java贪心算法的解题思路＋代码	2.09MB	9月前