Data mining

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Language: English
Cover of the book Data mining

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336 p. · 23.5x17.8 cm · Hardback
For courses in data mining.
Thorough in its coverage from basic to advanced topics, this text presents the algorithms and techniques used in data mining. It introduces readers to various data mining concepts and algorithms.
I. INTRODUCTION.
1. Introduction.
2. Related Concepts.
3. Data Mining Techniques.
II. CORE TOPICS.
4. Classification.
5. Clustering.
6. Association Rules.
III. ADVANCED TOPICS.
7. Web Mining.
8. Spatial Mining.
9. Temporal Mining.
IV. APPENDIX.
10. Data Mining Products.
  • A database perspective is used throughout, provides students with a focused discussion of algorithms, data structures, data types, and complexity of algorithms and space.
  • Clearly written algorithms, helps students to better understand techniques.
  • An emphasis on the use of data mining concepts in real world applications with large database components.
  • Appendix providing overview of available data mining products.
  • Strategic text organization of four major sections: Introduction, Core Topics, Advanced Topics, and Products, enables instructors to choose portions of the book to cover in a limited period of time.