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Understanding Complex Datasets: Data Mining with Matrix Decompositions (Anglais) Relié – 17 mai 2007


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Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book helps you determine which matrix is appropriate for your dataset and what the results mean.

Explaining the effectiveness of matrices as data analysis tools, the book illustrates the ability of matrix decompositions to provide more powerful analyses and to produce cleaner data than more mainstream techniques. The author explores the deep connections between matrix decompositions and structures within graphs, relating the PageRank algorithm of Google's search engine to singular value decomposition. He also covers dimensionality reduction, collaborative filtering, clustering, and spectral analysis. With numerous figures and examples, the book shows how matrix decompositions can be used to find documents on the Internet, look for deeply buried mineral deposits without drilling, explore the structure of proteins, detect suspicious emails or cell phone calls, and more.

Concentrating on data mining mechanics and applications, this resource helps you model large, complex datasets and investigate connections between standard data mining techniques and matrix decompositions.


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Couverture | Copyright | Table des matières | Extrait | Index | Quatrième de couverture
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13 internautes sur 14 ont trouvé ce commentaire utile 
Comprehensive and well-written! 26 novembre 2008
Par Michael Barnathan - Publié sur Amazon.com
Format: Relié Achat vérifié
I am doing research in data mining using tensor decompositions, and was very impressed by this book. It not only covers all of the important matrix and tensor decompositions, but also methods for computing them (with Matlab code!), the computational complexity of these methods, the tradeoffs and scenarios associated with each decomposition, and potential areas of application. To top it all off, the book is written in a highly approachable manner, covering the general concept of a decomposition and gradually discussing the specific decompositions from simplest to most complex. Highly recommended.
6 internautes sur 6 ont trouvé ce commentaire utile 
Solid, in-depth coverage of topics whose importance grows daily 15 mai 2011
Par Dan Brickley - Publié sur Amazon.com
Format: Relié
Clearly written and accessible to those with fading math skills, this book goes into useful detail, background and context that most online treatments skip past.
3 internautes sur 3 ont trouvé ce commentaire utile 
Leads with intuition always 5 novembre 2013
Par eldil - Publié sur Amazon.com
Format: Relié
If you want to understand matrix decomposition I doubt you could do better than this. He gives you 4 intuitive interpretations of decompositions; factor, composition, geometric, and graph. Something I love is that he doesn't just mention them once and then charge ahead with math; rather, he touches on them throughout the rest of the book, keeping intuition front and center.

His coverage of variants and applications is good as far as I can tell (you can 'search inside' for yourself). What he has covered (from 2007) is interesting enough to make you want to know the latest developments, but that's not a failing.

A note: the notation he uses is purely mathematical, not Matlab (Octave). He provides Matlab scripts in an appendix, and there is one slip-up where he uses Matlab notation (pg 32) in an equation, but it looks like a mere missed-cleanup; I don't recall, and flipping through it for this review I didn't see, any other places like it.
1 internautes sur 1 ont trouvé ce commentaire utile 
Clear, concise, to the point 14 mars 2012
Par Rutu Mulkar - Publié sur Amazon.com
Format: Relié Achat vérifié
I have been looking for a long time for a book to describe the intricacies of matrix decompositions, the theory and intuition behind it, and this book is the best one I have come across for that.

It describes the intuitions, the theory in a very easy to understand format.

I wish I had come across this book sooner.
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