Sprache: Englisch
Verlag: World Scientific Publishing Company, 2004
ISBN 10: 9812389229 ISBN 13: 9789812389220
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Sprache: Englisch
Verlag: World Scientific Publishing Company, Incorporated, 2004
ISBN 10: 9812389229 ISBN 13: 9789812389220
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 92,85
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In den WarenkorbZustand: New. pp. 331.
Sprache: Englisch
Verlag: World Scientific Pub Co Inc, 2004
ISBN 10: 9812389229 ISBN 13: 9789812389220
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 150,42
Anzahl: 1 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 331 pages. 9.00x6.25x1.00 inches. In Stock.
Sprache: Englisch
Verlag: World Scientific Publishing Company, 2004
ISBN 10: 9812389229 ISBN 13: 9789812389220
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 172,49
Anzahl: 2 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: WORLD SCIENTIFIC PUB CO INC, 2004
ISBN 10: 9812389229 ISBN 13: 9789812389220
Anbieter: moluna, Greven, Deutschland
Gebunden. Zustand: New. KlappentextrnrnIn 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 fo.
Sprache: Englisch
Verlag: World Scientific Publishing Company Aug 2004, 2004
ISBN 10: 9812389229 ISBN 13: 9789812389220
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - 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.