Knowledge Discovery and Data Mining
The Info-Fuzzy Network (IFN) Methodology
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Author
Contributions
- Last, Mark - Contributor
Publication
2001 - Springer US, Boston, MA, United States
Language
English
Word Count
42,000 words, Guess
Page Count
168 pages
Physical Format
Electronic resource
Identifiers
- Internet Archiveknowledgediscove00maim
- Internet Archiveknowledgediscove00maim_677
- ISBN-101441948422
- ISBN-101475732961
- ISBN-139781441948427
and 5 more
- ISBN-139781475732962
- OCLC Control Number851781335
- Better World Books9781441948427
- Better World Books9781475732962
- Open LibraryOL27067068M
Classifications
- DDC005.74
- LCCQA76.9.D35
- LCCQA75.5-76.95
Description
This book presents a unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network. The IFN methodology handles a selection of the most relevant features, extraction of informative rules and patterns, and post-processing of the extracted knowledge. This book provides detailed descriptions of the IFN algorithms and discusses real-world case studies from several application domains including manufacturing, process engineering, health care, and education. In addition, the book describes the methodology of applications and compares the IFN performance to other data mining methods. Audience: This book is intended to be used by researchers in the field of information systems, engineering, computer science, statistics, and management who are searching for a unified theoretical approach to the knowledge discovery process. The book can also serve as a reference book for courses on data mining, machine learning, and databases.
Subjects
Series Statement
- Massive Computing -- 1
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