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Download Max Bramer by Principles of Data Mining – Principles of Data Mining written by Max Bramer is very useful for Computer Science and Engineering (CSE) students and also who are all having an interest to develop their knowledge in the field of Computer Science as well as Information Technology. This Book provides an clear examples on each and every topics covered in the contents of the book to provide an every user those who are read to develop their knowledge.

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Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail.

This second edition has been expanded to include additional chapters on using frequent pattern trees for Association Rule Mining, comparing classifiers, ensemble classification and dealing with very large volumes of data.

Principles of Data Mining aims to help general readers develop the necessary understanding of what is inside the ‘black box’ so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.

Suitable as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science.

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Max Bramer

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