Data Mining: Concepts and Techniques eBook

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.

Data Mining: Concepts and TechniquesThis book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

• Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects
• Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields
• Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Additional ISBNs

1283171171, 0123814804, 9781283171175, 9780123814807

Data Mining: Concepts and Techniques 3rd Edition is written by Jiawei Han; Jian Pei; Micheline Kamber and published by Morgan Kaufmann. The Digital and eTextbook ISBNs for Data Mining: Concepts and Techniques are 9780123814807 and the print ISBNs are 9780123814791, 0123814790. Save up to 80% versus print by going digital with VitalSource. Additional ISBNs for this eTextbook include 1283171171, 0123814804, 9781283171175, 9780123814807.