Price: $56.79
(as of Nov 25, 2024 13:00:26 UTC – Details)
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.
Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projectsAddresses 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 fieldsProvides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
ASIN : B0058NBJ2M
Publisher : Morgan Kaufmann; 3rd edition (June 9, 2011)
Publication date : June 9, 2011
Language : English
File size : 12434 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 626 pages
Customers say
Customers find the book’s content great for understanding basic data mining concepts and explaining complex topics. However, some readers feel the content is dry and lacks real-world examples. Opinions are mixed on readability, with some finding it easy to read and well-written, while others say it’s difficult to read with excessive jargon and symbols.
AI-generated from the text of customer reviews
