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

Dan Simovici, Chabane Djeraba




[PDF.in03] Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

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 | #6098592 in Books |  2010-12-10 | Original language:English | PDF # 1 |  9.25 x1.42 x6.13l,1.92 | File type: PDF | 615 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||The maturing of the field of data mining has brought about an increased level of mathematical sophistication. Such disciplines like topology, combinatorics, partially ordered sets and their associated algebraic structures (lattices and Boole

This volume was born from the experience of the authors as researchers and educators,whichsuggeststhatmanystudentsofdataminingarehandicapped in their research by the lack of a formal, systematic education in its mat- matics. The data mining literature contains many excellent titles that address the needs of users with a variety of interests ranging from decision making to p- tern investigation in biological data. However, these books do not deal with the mathematical too...

You can specify the type of files you want, for your device.Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)   |  Dan Simovici, Chabane Djeraba.Not only was the story interesting, engaging and relatable, it also teaches lessons.

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