Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms)

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Lars Eldén 作者
Society for Industrial and Applied Mathematics
譯者
2007-04-09 出版日期
184 頁數
USD 69.00 價格
Paperback
叢書系列
9780898716269 圖書編碼

Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 圖書標籤: 數據挖掘  MATRIX  模式識彆  機器學習  數學  DataMining  矩陣論  矩陣   


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Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 著者簡介


Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 著者簡介


Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) 在線電子書 圖書描述

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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