模式分类
Pattern classification
Richard O. Duda、Peter E. Hart、David G. Stork · 初版 2001 年
8人推荐
9位读者提及
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“在语音识别、光学字符识别、图像处理或信号分析等众多不同应用领域中从事 pattern recognition 系统开发或研究的专业人员，常常面临着在令人眼花缭乱的现有技术中进行抉择的棘手任务。本独特的教科书兼专业参考书提供了为你挑选适于特定问题类别的最恰当方法所需的全部信息，对当今 pattern recognition 的核心主题进行了深入且系统的阐述。作为一部曾确立该领域发展基调的经典之作的全新版，
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最热门的选书基本是这几本：Murphy 的《Machine Learning: a Probabilistic Perspective》http://www.cs.ubc.ca/~murphyk/MLbook/，Duda 等人的《Pattern Classification》http://www.amazon.com/Pattern-Classification-Pt-1-Richard-Du...，Hastie 等人的《The Elements of Statistical Learning》（ESL），斯坦福有免费版 http://www-stat.stanford.edu/~tibs/ElemStatLearn…
The most popular choices seem to be: Machine Learning: a Probabilistic Perspective, by Murphy http://www.cs.ubc.ca/~murphyk/MLbook/ Pattern classification, by Duda et all http://www.amazon.com/Pattern-Classification-Pt-1-Richard-Du... The Elements of Statistical Learning, by Hastie et all. It is free from Stanford. http://www-stat.stanford.edu/~tibs/ElemStatLearn…
一本极好的入门教材是 Duda 和 Hart 的《Pattern Classification》http://www.amazon.com/Pattern-Classification-2nd-Richard-Dud...。写得很通俗易懂，对主流技术做了很好的概览。如果你想了解更多理论，可以试试 Cherkassky 和 Muller 的《Learning…
A great textbook as an intro is by Duda and Hart, Pattern Classification. http://www.amazon.com/Pattern-Classification-2nd-Richard-Dud.... Its pretty well written and gives a good overview of the main techniques. If you want a bit more theory, try Cherkassky and Muller, "Learning…
我随口能想到的有：- 汤姆·米歇尔的《Machine Learning》http://www.cs.cmu.edu/~tom/mlbook.html。通俗泛读和入门的话，我也很喜欢：- 理查德·杜达的《Pattern Classification》- 克里斯托弗·毕晓普的《Pattern Recognition and Machine Learning》（PRML）。如果想多偏重统计和数学，我通常会去啃《Classification,Parameter Estimation and State…
Of the top of my head, - Machine Learning by Tom M Mitchell http://www.cs.cmu.edu/~tom/mlbook.html For general reading and introductions I also like: - Pattern Classification by Richard Duda - Pattern Recognition and Machine Learning by Christopher Bishop For a bit more emphasis on statistics and math, I usually dive in to - Classification,Parameter Estimation and State…
…能免费看简直就是白送的福利。我还推荐《Elements of Statistical Learning》（ESL）：http://www-stat.stanford.edu/~tibs/ElemStatLearn/，以及 Duda、Hart 和 Stork 写的《Pattern Classification》：http://rii.ricoh.com/~stork/DHS.html
…fact that it's available for free is just an added bonus. I would also suggest Elements of Statistical Learning: http://www-stat.stanford.edu/~tibs/ElemStatLearn/ As well as Duda, Hart, and Stork's Pattern Classification: http://rii.ricoh.com/~stork/DHS.html
…代数、数值计算/优化（凸优化、非线性优化）、统计推断、随机过程。不错的参考书：1) 《Elements of Statistical Learning》- Hastie、Tibshirani 和 Friedman 2) 《Pattern Classification》- Duda、Hart 和 Stork 3) 《Pattern Recognition》- Theoridis、Koutroumbas 4) 《Machine Learning》- Tom Mitchell 5) http://videolectures.net/Top/Computer_Science/Machine_Learni...
…Algebra, Numerical Computation/Optimization (Convex, Nonlinear), Statistical Inference, Stochastic Processes. Good References: 1) Elements of Statistical Learning - Hastie, Tibshirani and Friedman 2) Pattern Classification - Duda, Hart and Stork 3) Pattern Recognition - Theoridis, Koutroumbas 4) Machine Learning - Tom Mitchell 5) http://videolectures.net/Top/Computer_Science/Machine_Learni...
没错，Duda、Hart 和 Stork 写的《Pattern Classification》：http://www.amazon.com/Pattern-Classification-2nd-Richard-Dud...，非常接地气实用，涵盖了许多机器学习和人工智能主题的算法（从…
Yep, Pattern Classification by Duda, Hart and Stork: http://www.amazon.com/Pattern-Classification-2nd-Richard-Dud... It is very pragmatic, including algorithms for many machine learning and artificial intelligence topics (from…