Könyv Matrix Methods in Data Mining and Pattern Recognition Lars Elden

Matrix Methods in Data Mining and Pattern Recognition

Szerző: Lars Elden
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: 50 % esély
Keressük az egész világon
33 946 Ft
Several very powerful numerical linear algebra techniques are available for solving problems in data...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2007
oldal
235
EAN
9780898716269
ISBN
0898716268
Enbook ID
04379382
Súly
424
Méretek
151 x 254 x 14

Teljes leírás

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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