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008 110705s2011 fluad sb 001 0 eng d
020 _a9781439821282 (ebook : PDF)
040 _aFlBoTFG
_cFlBoTFG
090 _aQ325.5
_b.L54 2011
092 _a542.85
_bL693
100 1 _aLiang, Yizeng.
245 1 0 _aSupport vector machines and their application in chemistry and biotechnology
_h[electronic resource] /
_cYizeng Liang ... [et al.].
260 _aBoca Raton, Fla. :
_bCRC Press,
_c2011.
300 _ax, 201 p. :
_bill.
504 _aIncludes bibliographical references and index.
505 0 _ach. 1. Overview of support vector machines -- ch. 2. Support vector machines for classification and regression -- ch. 3. Kernel methods -- ch. 4. Ensemble learning of support vector machines -- ch. 5. Support vector machines applied to near-infrared spectroscopy -- ch. 6. Support vector machines and QSAR/QSPR -- ch. 7. Support vector machines applied to traditional Chinese medicine -- ch. 8. Support vector machines applied to OMICS study.
520 _a"Support vector machines (SVMs), a promising machine learning method, is a powerful tool for chemical data analysis and for modeling complex physicochemical and biological systems. It is of growing interest to chemists and has been applied to problems in such areas as food quality control, chemical reaction monitoring, metabolite analysis, QSAR/QSPR, and toxicity. This book presents the theory of SVMs in a way that is easy to understand regardless of mathematical background. It includes simple examples of chemical and OMICS data to demonstrate the performance of SVMs and compares SVMs to other traditional classification/regression methods"--
_cProvided by publisher.
530 _aAlso available in print edition.
538 _aMode of access: World Wide Web.
650 0 _aSupport vector machines.
650 0 _aChemometrics.
655 7 _aElectronic books.
_2lcsh
776 1 _z9781439821275
856 4 0 _uhttp://marc.crcnetbase.com/isbn/9781439821282
_qapplication/PDF
_zDistributed by publisher. Purchase or institutional license may be required for access.
999 _c15550
_d15550