| 000 | 01010camuu2200289 a 4500 | |
| 001 | 000045300542 | |
| 005 | 20061025102953 | |
| 008 | 980707s1998 maua b 001 0 eng | |
| 010 | ▼a 98029384 | |
| 020 | ▼a 0792382528 (alk. paper) | |
| 035 | ▼a (KERIS)REF000004787443 | |
| 040 | ▼a DLC ▼c DLC ▼d DLC ▼d 211009 | |
| 050 | 0 0 | ▼a QA76.9.D3 ▼b C495 1998 |
| 082 | 0 0 | ▼a 006.3 ▼2 21 |
| 090 | ▼a 006.3 ▼b C576d | |
| 100 | 1 | ▼a Cios, Krzysztof J. |
| 245 | 1 0 | ▼a Data mining methods for knowledge discovery / ▼c by Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski. |
| 260 | ▼a Boston : ▼b Kluwer Academic , ▼c c1998. | |
| 300 | ▼a xxi, 495 p. : ▼b ill. ; ▼c 25 cm. | |
| 440 | 4 | ▼a The Kluwer international series in engineering and computer science ; ▼v SECS 458 |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Database management. |
| 650 | 0 | ▼a Data mining. |
| 700 | 1 | ▼a Pedrycz, Witold ▼d 1953- |
| 700 | 1 | ▼a S>winiarski, Roman. |
| 945 | ▼a KINS |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 중앙도서관/서고6층/ | 청구기호 006.3 C576d | 등록번호 111382587 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
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.
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.
정보제공 :
목차
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.
정보제공 :