A01=Zhengxin Chen
algorithms
art
author
Author_Zhengxin Chen
Category=UN
Category=UYQ
concentrates
data
data miningsuch
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
expert
fields
guide
infrastructure
issues
mining
practical aspects
processesbut
range
several
specifically
state
summarizing
topics
uncertain
vital
volume
wide
Product details
- ISBN 9780471388784
- Weight: 674g
- Dimensions: 159 x 241mm
- Publication Date: 05 Oct 2001
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Hardback
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An expert guide for applying data mining with uncertain reasoning to a wide range of uses
This volume presents a holistic view of data mining by integrating this diverse and exciting field with uncertain reasoning. It treats a wide range of issues and examines the state of the art in both fields while summarizing vital concepts that can normally only be found in various separate resources.
The author concentrates on practical aspects of data mining-such as infrastructure and overall processes-but also discusses some selected algorithms and performance-related issues. Several important topics are addressed specifically, such as bridging the fields of machine learning and data mining and the discovery of influential association rules. In addition, the author discusses data warehousing as an enabling technique for data mining. Case studies are included throughout to illustrate important concepts.
Data Mining and Uncertain Reasoning is a practical reference for practitioners in various interrelated fields. Each subject is treated with both basic introductory and advanced technical descriptions, making the book suitable for students and practitioners at various levels of experience.
This volume presents a holistic view of data mining by integrating this diverse and exciting field with uncertain reasoning. It treats a wide range of issues and examines the state of the art in both fields while summarizing vital concepts that can normally only be found in various separate resources.
The author concentrates on practical aspects of data mining-such as infrastructure and overall processes-but also discusses some selected algorithms and performance-related issues. Several important topics are addressed specifically, such as bridging the fields of machine learning and data mining and the discovery of influential association rules. In addition, the author discusses data warehousing as an enabling technique for data mining. Case studies are included throughout to illustrate important concepts.
Data Mining and Uncertain Reasoning is a practical reference for practitioners in various interrelated fields. Each subject is treated with both basic introductory and advanced technical descriptions, making the book suitable for students and practitioners at various levels of experience.
ZHENGXIN CHEN is Professor in the Department of Computer Science at the University of Nebraska.
