Practical applications of data mining

Various topics of data mining techniques are identified and described throughout, including clustering, association rules, rough set theory, probability theory, neural networks, classification, and fuzzy logic. Each of these techniques is explored with a theoretical introduction and its effectivenes...

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Bibliographic Details
Main Author: Suh, Sang C. (Author)
Format: Book
Language:English
Published: Sudbury, Massachusetts : Jones & Bartlett Learning , c2012
Subjects:

MARC

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020 |a 0763785873 (paperback : alk. paper) 
020 |a 9780763785871 (paperback : alk. paper) 
050 0 0 |a QA76.9.D343   |b S84 2012 
090 0 0 |a QA76.9.D343   |b S84 2012 
100 1 |a Suh, Sang C. ,   |e author 
245 1 0 |a Practical applications of data mining   |c Sang C. Suh 
260 |a Sudbury, Massachusetts :   |b Jones & Bartlett Learning ,   |c c2012 
300 |a xx, 414 p. :   |b ill. ;   |c 24 cm. 
500 |a Includes bibliographical references and index 
505 0 |a 1. Introduction to data mining -- 2. Association rules -- 3. Classification learning -- 4. Statistics for data mining -- 5. Rough sets and bayes theories -- 6. Neural networks -- 7. Clustering -- 8. Fuzzy information retrieval 
520 |a Various topics of data mining techniques are identified and described throughout, including clustering, association rules, rough set theory, probability theory, neural networks, classification, and fuzzy logic. Each of these techniques is explored with a theoretical introduction and its effectiveness is demonstrated with various chapter examples 
650 0 |a Data mining 
999 |a 1000152283   |b Book   |c OPEN SHELF (30 DAYS)   |e Tembila Campus