Soft Computing for Knowledge Discovery and Data Mining (eBook)

Oded Maimon, Lior Rokach (Herausgeber)

eBook Download: PDF

2007 | 2008
XIII, 433 Seiten
Springer US (Verlag)
978-0-387-69935-6 (ISBN)

Infos

Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability.

This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

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Data mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability.Soft Computing for Knowledge Discovery and Data Mining introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining. This edited volume by highly regarded authors, includes several contributors of the 2005, Data Mining and Knowledge Discovery Handbook.  This book was written to provide investigators in the fields of information systems, engineering, computer science, statistics and management with a profound source for the role of soft computing in data mining. Not only does this book feature illustrations of various applications including manufacturing, medical, banking, insurance and others, but also includes various real-world case studies with detailed results.Soft Computing for Knowledge Discovery and Data Mining is designed for practitioners and researchers in industry. Practitioners and researchers may be particularly interested in the description of real world data mining projects performed with soft computing. This book is also suitable as a secondary textbook or reference for advanced-level students in information systems, engineering, computer science and statistics management.  

Inhalt

Preface 6
Contents 8
List of Contributors 10
Introduction to Soft Computing for Knowledge Discovery and Data Mining 13
Neural Network Methods 26
Neural Networks For Data Mining 27
Improved SOM Labeling Methodology for Data Mining Applications 55
Evolutionary Methods 86
A Review of Evolutionary Algorithms for Data Mining 87
Genetic Clustering for Data Mining 120
Discovering New Rule Induction Algorithms with Grammar-based Genetic Programming 140
Evolutionary Design of Code-matrices for Multiclass Problems 160
Fuzzy Logic Methods 192
The Role of Fuzzy Sets in Data Mining 193
Support Vector Machines and Fuzzy Systems 210
KDD in Marketing with Genetic Fuzzy Systems 229
Knowledge Discovery in a Framework for Modelling with Words 244
Advanced Soft Computing Methods and Areas 280
Swarm Intelligence Algorithms for Data Clustering 281
A Diffusion Framework for Dimensionality Reduction 316
Data Mining and Agent Technology: a fruitful symbiosis 327
Approximate Frequent Itemset Mining In the Presence of Random Noise 363
The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining 390
Index 431

Produkt-Details

• Erscheint lt. Verlag: 25.10.2007
• Zusatzinfo: XIII, 433 p.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Mathematik / Informatik ► Informatik ► Netzwerke
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Informatik ► Weitere Themen ► Hardware
• Schlagworte: algorithms • Bayesian Network • classification • Clustering • Data Mining • Dom • evolutionary algorithm • fuzzy • genetic programming • information system • Intelligence • Knowledge Discovery • Maimon • Rokach • Soft Computing • Support Vector Machine
• ISBN-10: 0-387-69935-X / 038769935X
• ISBN-13: 978-0-387-69935-6 / 9780387699356