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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

Dan A. Simovici, Chabane Djeraba




[PDF.pw91] Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

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 | #4730678 in Books |  2014-03-27 | Original language:English | PDF # 1 |  9.20 x1.90 x6.20l,2.75 | File type: PDF | 831 pages

||1 of 1 people found the following review helpful.| Vast, dense, and concise|By Joseph A. Dudar|It's correct that this book has typesetting errors in the symbolic math. After sampling and exploring various regions of the book I only found one section with an error: the set theoretical foundational material. I have may books that start this way, and it's useful to see the notation and concepts the author will use later in the boo|From the Back Cover||Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book.  Topics include partially ordered sets, combinatorics,  general topology, metric spaces, linear sp

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book...

You easily download any file type for your gadget.Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)   |  Dan A. Simovici, Chabane Djeraba. A good, fresh read, highly recommended.

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