Data mining methods for knowledge discovery

著者

• Cios, Krzysztof J.
• Pedrycz, Witold
• Świniarski, Roman

書誌事項

Data mining methods for knowledge discovery

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

（The Kluwer international series in engineering and computer science, SECS 458）

Kluwer Academic, c1998

注記

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

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.

「Nielsen BookData」 より

詳細情報

• NII書誌ID(NCID): BA3832258X
• ISBN:
  • 0792382528
• LCCN: 98029384
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Boston, Mass
• ページ数/冊数: xxi, 495 p.
• 大きさ: 25 cm
• 分類:
  • LCC : QA76.9.D3
  • DC21 : 006.3
• 件名:
  • LCSH : Database management
  • LCSH : Data mining
• 親書誌ID:
  • BA0004729X