SØG - mellem flere end 8 millioner bøger:
Viser: Data Mining and Analysis - Fundamental Concepts and Algorithms
Data Mining and Analysis
Fundamental Concepts and Algorithms
Mohammed J. Zaki og Wagner Meira
(2014)
Sprog: Engelsk
Cambridge University Press
744,00 kr.
Bogen er udgået og er erstattet af nyere udgave
Detaljer om varen
- Hardback: 562 sider
- Udgiver: Cambridge University Press (Maj 2014)
- Forfattere: Mohammed J. Zaki og Wagner Meira
- ISBN: 9780521766333
The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics. This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, algorithmic perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike.
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 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.
De oplyste priser er inkl. moms
Butikker og åbningstid
Handler du som firma
Forretningsbetingelser
Porto og forsendelse
Data & cookiepolitik
Handler du som firma
Forretningsbetingelser
Porto og forsendelse
Data & cookiepolitik
Find pensumliste
FAQ for studerende
Pensumlistegaranti
Sortiment og levering
Kompendier(for undervisere)
FAQ for studerende
Pensumlistegaranti
Sortiment og levering
Kompendier(for undervisere)
Polyteknisk Boghandel og Forlag A/S - Anker Engelundsvej 1 - 2800 Lyngby
Tlf 77 42 43 44 - email poly@polyteknisk.dk - CVR 34072655 - Sydbank Reg: 6748 Konto 0001107927
Tlf 77 42 43 44 - email poly@polyteknisk.dk - CVR 34072655 - Sydbank Reg: 6748 Konto 0001107927