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

Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms) pdf epub mobi txt 電子書 下載2025

出版者:Society for Industrial and Applied Mathematics
作者:Lars Eldén
出品人:
頁數:184
译者:
出版時間:2007-04-09
價格:USD 69.00
裝幀:Paperback
isbn號碼:9780898716269
叢書系列:
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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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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