Data Mining Methods for Knowledge Discovery / Edition 1

Data Mining Methods for Knowledge Discovery / Edition 1

by Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski
     
 

ISBN-10: 0792382528

ISBN-13: 9780792382522

Pub. Date: 08/31/1998

Publisher: Springer US

Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and…  See more details below

Overview

Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography.
Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.

Product Details

ISBN-13:
9780792382522
Publisher:
Springer US
Publication date:
08/31/1998
Series:
The Springer International Series in Engineering and Computer Science, #458
Edition description:
1998
Pages:
495
Product dimensions:
6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

Foreword. Preface. 1. Data Mining and Knowledge Discovery. 2. Rough Sets. 3. Fuzzy Sets. 4. Bayesian Methods. 5. Evolutionary Computing. 6. Machine Learning. 7. Neural Networks. 8. Clustering. 9. Preprocessing. Index.

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