| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000046074214 | |
| 005 | 20210317121851 | |
| 008 | 210317s2020 enka 001 0 eng | |
| 010 | ▼a 2019037293 | |
| 020 | ▼a 9781108473989 (hardback) | |
| 020 | ▼a 9781108564175 (epub) | |
| 035 | ▼a (KERIS)REF000019134955 | |
| 040 | ▼a DLC ▼b eng ▼e rda ▼c DLC ▼d 211009 | |
| 042 | ▼a pcc | |
| 050 | 0 0 | ▼a QA76.9.D343 ▼b Z36 2020 |
| 082 | 0 0 | ▼a 006.3/12 ▼2 23 |
| 084 | ▼a 006.312 ▼2 DDCK | |
| 090 | ▼a 006.312 ▼b Z21d2 | |
| 100 | 1 | ▼a Zaki, Mohammed J., ▼d 1971- ▼e author. |
| 240 | 1 0 | ▼a Data mining and analysis |
| 245 | 1 0 | ▼a Data mining and machine learning : ▼b fundamental concepts and algorithms / ▼c Mohammed J. Zaki, Wagner Meira, Jr. |
| 250 | ▼a 2nd ed. | |
| 260 | ▼a Cambridge, United Kingdom ; New York, NY : ▼b Cambridge University Press, ▼c 2020. | |
| 300 | ▼a xii, 766 p. : ▼b ill. ; ▼c 26 cm. | |
| 336 | ▼a text ▼b txt ▼2 rdacontent | |
| 337 | ▼a unmediated ▼b n ▼2 rdamedia | |
| 338 | ▼a volume ▼b nc ▼2 rdacarrier | |
| 500 | ▼a Revised edition of: Data mining and analysis. 2014. | |
| 500 | ▼a Includes index. | |
| 520 | ▼a "The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts.New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning"-- ▼c Provided by publisher. | |
| 650 | 0 | ▼a Data mining. |
| 700 | 1 | ▼a Meira, Wagner, ▼d 1967-, ▼e author. |
| 945 | ▼a KLPA |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.312 Z21d2 | 등록번호 121256771 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
목차
1. Data mining and analysis; Part I. Data Analysis Foundations: 2. Numeric attributes; 3. Categorical attributes; 4. Graph data; 5. Kernel methods; 6. High-dimensional data; 7. Dimensionality reduction; Part II. Frequent Pattern Mining: 8. Itemset mining; 9. Summarizing itemsets; 10. Sequence mining; 11. Graph pattern mining; 12. Pattern and rule assessment; Part III. Clustering: 13. Representative-based clustering; 14. Hierarchical clustering; 15. Density-based clustering; 16. Spectral and graph clustering; 17. Clustering validation; Part IV. Classification: 18. Probabilistic classification; 19. Decision tree classifier; 20. Linear discriminant analysis; 21. Support vector machines; 22. Classification assessment; Part V. Regression: 23. Linear regression; 24. Logistic regression; 25. Neural networks; 26. Deep learning; 27. Regression evaluation.