Data Mining: Concepts and Techniques 3/e (H)
- 20本以上，享 8.5折
售價
$
1,350
- 一般書籍
- ISBN：9780123814791
- 作者：Han
- 版次：3
- 年份：2011
- 出版商：Elsevier B.V.
- 頁數/規格：703頁/精裝單色
書籍介紹
目錄
Description
The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it’s still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge.
Since the previous edition’s publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniquescontinue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today’s most powerful data mining techniques to meet real business challenges.
The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it’s still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge.
Since the previous edition’s publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniquescontinue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today’s most powerful data mining techniques to meet real business challenges.
Table of Contents
Chapter 1. Introduction
Chapter 2. Getting to Know Your Data
Chapter 3. Data Preprocessing
Chapter 4. Data Warehousing and Online Analytical Processing
Chapter 5. Data Cube Technology
Chapter 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods
Chapter 7. Advanced Pattern Mining
Chapter 8. Classification: Basic Concepts
Chapter 9. Classification: Advanced Methods
Chapter 10. Cluster Analysis: Basic Concepts and Methods
Chapter 11. Advanced Cluster Analysis
Chapter 12. Outlier Detection
Chapter 13. Data Mining Trends and Research Frontiers
Chapter 1. Introduction
Chapter 2. Getting to Know Your Data
Chapter 3. Data Preprocessing
Chapter 4. Data Warehousing and Online Analytical Processing
Chapter 5. Data Cube Technology
Chapter 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods
Chapter 7. Advanced Pattern Mining
Chapter 8. Classification: Basic Concepts
Chapter 9. Classification: Advanced Methods
Chapter 10. Cluster Analysis: Basic Concepts and Methods
Chapter 11. Advanced Cluster Analysis
Chapter 12. Outlier Detection
Chapter 13. Data Mining Trends and Research Frontiers
