Soft Computing for Knowledge Discovery and Data Mining

Name: Soft Computing for Knowledge Discovery and Data Mining
Brand: Springer-Verlag New York Inc.
SKU: 9780387699349
Price: 297.23 RON
Availability: InStock

Autor: Oded Maimon, Lior Rokach

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Legare: Copertă tare

Editura: Springer-Verlag New York Inc.

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Data mining is the science and technology of exploring large and complex bodies of data in order to...

Informații despre carte

Autor

Oded Maimon, Lior Rokach

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2007

Pagini

433

EAN

9780387699349

ISBN

0387699341

Enbook ID

01382367

Editura

Springer-Verlag New York Inc.

Greutate

829

Dimensiuni

155 x 235 x 34

Descriere completă

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.

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