Data Mining and Knowledge Discovery with Evolutionary Algorithms / Edition 1

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Overview

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
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Editorial Reviews

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"In the snappily-titled Data Mining and Knowledge Discovery with Evolutionary Algorithms, leading researcher Alex A Freitas introduces both data mining and evolutionary algorithms. … The aim is to introduce and address the key challenges to a high level of detail. With an understanding gleaned from this book, and source code available freely on the web, the world of data mining is your oyster." (Application Development Advisor, January/February, 2003)

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Product Details

  • ISBN-13: 9783540433316
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 10/3/2002
  • Series: Natural Computing Series
  • Edition description: 2002
  • Edition number: 1
  • Pages: 265
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.69 (d)

Table of Contents

1 Introduction 1
2 Data Mining Tasks and Concepts 13
3 Data Mining Paradigms 45
4 Data Preparation 65
5 Basic Concepts of Evolutionary Algorithms 79
6 Genetic Algorithms for Rule Discovery 107
7 Genetic Programming for Rule Discovery 139
8 Evolutionary Algorithms for Clustering 165
9 Evolutionary Algorithms for Data Preparation 179
10 Evolutionary Algorithms for Discovering Fuzzy Rules 205
11 Scaling up Evolutionary Algorithms for Large Data Sets 233
12 Conclusions and Research Directions 255
Index 263
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