Data mining : concepts and techniques / Jiawei Han, Micheline Kamber, Jian Pei.
Language: English Publisher: Waltham, Mass. Elsevier/Morgan Kaufmann, cop. 2012Edition: third editionDescription: xxxv, 703 sidor illustrationer 25 cmISBN:- 9780123814791
- 0123814790
- 006.312 22/swe
- QA76.9.D343
- Pud
Item type | Current library | Shelving location | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Dayloan | Biblioteket HKR | Biblioteket | 006.3 Han | Available | 11156000189226 | |||
Course literature | Biblioteket HKR | Biblioteket | 006.3 Han | Available | 11156000188836 | |||
Course literature | Biblioteket HKR | Biblioteket | 006.3 Han | Available | 11156000188837 |
Enhanced descriptions from Syndetics:
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining.
This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.
Includes bibliographical references and index
Table of contents provided by Syndetics
- Chapter 1 Introduction
- Chapter 2 Getting to Know Your Data
- Chapter 3 Preprocessing
- Chapter 4 Data Warehousing and On-Line Analytical Processing
- Chapter 5 Data Cube Technology
- Chapter 6 Mining Frequent Patterns, Associations and Correlations: Concepts and Methods
- Chapter 7 Advanced Frequent 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 Analysis
- Chapter 13 Data Mining Trends and Research Frontiers in Data Mining