Matrix Methods in Data Mining and Pattern Recognition

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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.
The applications discussed in the book are classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition.
The book is intended for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.

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关键词：Recognition Data Mining cognition Pattern Methods matrix Mining Data Recognition Pattern

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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.

要是不收费就更好了

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很好的东西,要是不收钱就好了!