Lecture Notes in Data Mining

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Michael W. Berry, Murray Browne
World Scientific, Jan 1, 2006 - Computers - 222 pages
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The continual explosion of information technology and the need for better data collection and management methods has made data mining an even more relevant topic of study. Books on data mining tend to be either broad and introductory or focus on some very specific technical aspect of the field. This book is a series of seventeen edited "student-authored lectures" which explore in depth the core of data mining (classification, clustering and association rules) by offering overviews that include both analysis and insight. The initial chapters lay a framework of data mining techniques by explaining some of the basics such as applications of Bayes Theorem, similarity measures, and decision trees. Before focusing on the pillars of classification, clustering and association rules, the book also considers alternative candidates such as point estimation and genetic algorithms.

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About the author (2006)

Murray Browne has written literary essays and reviews and co-authored *Understanding Search Engines: Mathematical Modeling and Text Retrieval*. Browne grew up in East Central, Illinois, graduated from Indiana University, and earned a Masters in Information Sciences from the University of Tennessee. Proud father of two grown daughters, Browne lives in Atlanta and works as Media Content Analyst for Turner Broadcasting.

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