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Viser: Support Vector Machine in Chemistry
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SUPPORT VECTOR MACHINE IN CHEMISTRY Vital Source e-bog
Chen Nianyi
(2004)
World Scientific Publishing
2.457,00 kr.
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Support Vector Machine in Chemistry
Nianyi Chen, Wencong Lu, Jie Yang og Guozheng Li
(2004)
Sprog: Engelsk
World Scientific Publishing Co Pte Ltd
1.712,00 kr.
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Detaljer om varen
- Vital Source searchable e-book (Fixed pages)
- Udgiver: World Scientific Publishing (August 2004)
- ISBN: 9789812794710
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.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Hardback: 350 sider
- Udgiver: World Scientific Publishing Co Pte Ltd (August 2004)
- Forfattere: Nianyi Chen, Wencong Lu, Jie Yang og Guozheng Li
- ISBN: 9789812389220
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.
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