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matrix methods in data mining and pattern recognition.pdf

The first version of this book was a set of lecture notes for a graduate course on data mining and applications in science and technology organized by the Swedish National Graduate School in Scientific Computing (NGSSC). Since then the material has been used and further developed for an undergraduate course on numerical algorithms for data mining and IT at Link¨oping University. This is a second course in scientific computing for computer science students.
2011-11-15 上传大小:17.93MB
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评论 共18条

wyhlucky 入门书,可以看一看,打打基础。
2015-07-17
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qintxx 讲解非常清楚,有用!
2015-07-13
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oaaronramsey 很好的书,非常有用 谢谢
2015-01-04
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belenob 看到这本书很意外,看了以后觉得写的很好,适合入门研究生
2014-12-17
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rangohu 有些笔误什么的,感觉不是个很好的版本。
2014-09-20
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bzljn 前不久下载的,很好。
2014-08-28
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a391827325 好资源, 找了好久了,矩阵论方法可以处理大规模数据挖掘问题
2014-07-09
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hutwangzm2008 非常好的东西,对我现在的研究课题很有帮助,谢谢
2013-12-23
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swiftcore 是一本不错的好书
2013-12-12
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zhongguodianke 矩阵角度的机器学习,角度不错,不过内容似乎有点单薄
2013-10-24
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matrix methods in data mining and pattern recognition

Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.

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