Advanced Data Mining Techniques / Edition 1

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Overview

This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.

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Editorial Reviews

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"Text analysis and data mining have become increasingly important capabilities in today’s information-flooded world, and choosing the right technique makes all the difference. This book contains some advanced data mining techniques, but also includes an overview of important data mining fundamentals, specifically the CRISP-DM and SEMMA industry standards. … Summing Up: Recommended. Upper-division undergraduates and up." (H. J. Bender, CHOICE, Vol. 45 (11), August, 2008)

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Product Details

  • ISBN-13: 9783540769163
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 3/4/2008
  • Edition description: 2008
  • Edition number: 1
  • Pages: 180
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.42 (d)

Table of Contents

Data Mining Process.- Data Mining Methods As Tools.- Memory-Based Reasoning Methods.- Association Rules in Knowledge Discovery.- Fuzzy Sets in Data Mining.- Rough Sets.- Support Vector Machines.- Genetic Algorithm Support to Data Mining.- Performance Evaluation for Predictive Modeling.- Applications.- Applications of Methods.
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