A01=Guozheng Li
A01=Jie Yang
A01=Nianyi Chen
A01=Wencong Lu
Author_Guozheng Li
Author_Jie Yang
Author_Nianyi Chen
Author_Wencong Lu
Category=PN
Category=UYQM
Data Mining
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eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Machine Learning
Materials Design
Optimization
Pattern Recognition
Structure-Activity Relationship
StructureAcAEURA"Activity Relationship
Structure–Activity Relationship
Support Vector Classification
Support Vector Machine
Support Vector Regression
Product details
- ISBN 9789812389220
- Publication Date: 25 Aug 2004
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
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In recent years, the support vector machine (SVM), a new data processing method, has been applied to many fields of chemistry and chemical technology. Compared with some other data processing methods, SVM is especially suitable for solving problems of small sample size, with superior prediction performance. SVM is fast becoming a powerful tool of chemometrics. This book provides a systematic approach to the principles and algorithms of SVM, and demonstrates the application examples of SVM in QSAR/QSPR work, materials and experimental design, phase diagram prediction, modeling for the optimal control of chemical industry, and other branches in chemistry and chemical technology.
