Cargando…
Support vector machines and their application in chemistry and biotechnology /
"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, chem...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press,
2011.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a2200000 a 4500 | ||
|---|---|---|---|
| 001 | OR_ocn729371391 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 110607s2011 fluh ob 001 0 eng d | ||
| 040 | |a N$T |b eng |e pn |c N$T |d YDXCP |d E7B |d OCLCQ |d FXR |d OHS |d OCLCQ |d UIU |d OCLCQ |d DEBSZ |d OCLCQ |d UIU |d UMI |d DEBBG |d OTZ |d OCLCF |d CRCPR |d IDEBK |d UA@ |d OCLCQ |d VT2 |d CEF |d COO |d UWO |d YDX |d ESU |d K6U |d OCLCO |d OCLCQ |d OCLCO |d OCLCQ |d OCL |d SFB |d OCLCQ | ||
| 015 | |a GBB0A8118 |2 bnb | ||
| 016 | 7 | |a 015644732 |2 Uk | |
| 019 | |a 759865834 |a 880372993 |a 1008953846 |a 1067231608 |a 1077296510 |a 1084344055 |a 1156371789 |a 1192336320 |a 1240534068 | ||
| 020 | |a 9781439821282 |q (electronic bk.) | ||
| 020 | |a 1439821283 |q (electronic bk.) | ||
| 020 | |z 9781439821275 | ||
| 020 | |z 1439821275 | ||
| 024 | 7 | |a 10.1201/b10911 |2 doi | |
| 029 | 1 | |a AU@ |b 000065155629 | |
| 029 | 1 | |a DEBBG |b BV042032574 | |
| 029 | 1 | |a DEBSZ |b 372821871 | |
| 029 | 1 | |a DEBSZ |b 414180445 | |
| 029 | 1 | |a NZ1 |b 14091723 | |
| 029 | 1 | |a NZ1 |b 14091726 | |
| 029 | 1 | |a NZ1 |b 14939780 | |
| 035 | |a (OCoLC)729371391 |z (OCoLC)759865834 |z (OCoLC)880372993 |z (OCoLC)1008953846 |z (OCoLC)1067231608 |z (OCoLC)1077296510 |z (OCoLC)1084344055 |z (OCoLC)1156371789 |z (OCoLC)1192336320 |z (OCoLC)1240534068 | ||
| 037 | |a CL0500000429 |b Safari Books Online | ||
| 050 | 4 | |a Q325.5 |b .S866 2011eb | |
| 060 | 4 | |a QU 26.5 | |
| 072 | 7 | |a SCI |x 013020 |2 bisacsh | |
| 082 | 0 | 4 | |a 542/.85 |2 22 |
| 084 | |a COM000000 |a MED009000 |a SCI013050 |2 bisacsh | ||
| 049 | |a UAMI | ||
| 245 | 0 | 0 | |a Support vector machines and their application in chemistry and biotechnology / |c Yizeng Liang [and others]. |
| 260 | |a Boca Raton, FL : |b CRC Press, |c 2011. | ||
| 300 | |a 1 online resource (x, 193 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 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"-- |c Provided by publisher | ||
| 520 | |a "Support vector machines (SVMs) seem a very promising kernel-based machine learning method originally developed for pattern recognition and later extended to multivariate regression. What distinguishes SVMs from traditional learning methods lies in its exclusive objective function, which minimizes the structural risk of the model. The introduction of the kernel function into SVMs made it extremely attractive, since it opens a new door for chemists/biologists to use SVMs to solve difficult nonlinear problems in chemistry and biotechnology through the simple linear transformation technique. The distinctive features and excellent empirical performances of SVMs have drawn the eyes of chemists and biologists so much that a number of papers, mainly concerned with the applications of SVMs, have been published in chemistry and biotechnology in recent years. These applications cover a large scope of chemical and/or biological meaningful problems, e.g. spectral calibration, drug design, quantitative structure-activity/property relationship (QSAR/QSPR), food quality control, chemical reaction monitoring, metabolic fingerprint analysis, protein structure and function prediction, microarray data-based cancer classification and so on. However, in order to efficiently apply this rather new technique to solve difficult problems in chemistry and biotechnology, one should have a sound in-depth understanding of what kind information this new mathematical tool could really provide and what its statistic property is. This book aims at giving a deeper and more thorough description of the mechanism of SVMs from the point of view of chemists/biologists and hence to make it easy for chemists and biologists to understand"-- |c Provided by publisher | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a ch. 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. | |
| 588 | 0 | |a Print version record. | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Support vector machines. | |
| 650 | 0 | |a Chemometrics. | |
| 650 | 0 | |a Chemistry. | |
| 650 | 0 | |a Linear programming. | |
| 650 | 2 | |a Chemistry | |
| 650 | 2 | |a Biotechnology | |
| 650 | 2 | |a Programming, Linear | |
| 650 | 6 | |a Machines à vecteurs supports. | |
| 650 | 6 | |a Chimiométrie. | |
| 650 | 6 | |a Chimie. | |
| 650 | 6 | |a Biotechnologie. | |
| 650 | 6 | |a Programmation linéaire. | |
| 650 | 7 | |a chemistry. |2 aat | |
| 650 | 7 | |a bioengineering. |2 aat | |
| 650 | 7 | |a Linear programming. |2 fast |0 (OCoLC)fst00999090 | |
| 650 | 7 | |a Chemistry. |2 fast |0 (OCoLC)fst00853344 | |
| 650 | 7 | |a Chemometrics. |2 fast |0 (OCoLC)fst01736550 | |
| 650 | 7 | |a Support vector machines. |2 fast |0 (OCoLC)fst01747369 | |
| 700 | 1 | |a Liang, Yizeng. | |
| 776 | 0 | 8 | |i Print version: |t Support vector machines and their application in chemistry and biotechnology. |d Boca Raton, FL : CRC Press, 2011 |z 9781439821275 |w (DLC) 2010041498 |w (OCoLC)663445103 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781439821282/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a CRC Press |b CRCP |n CRC0KE11001PDF | ||
| 938 | |a ebrary |b EBRY |n ebr10469410 | ||
| 938 | |a EBSCOhost |b EBSC |n 367215 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis30545755 | ||
| 938 | |a YBP Library Services |b YANK |n 3497629 | ||
| 938 | |a YBP Library Services |b YANK |n 15914740 | ||
| 994 | |a 92 |b IZTAP | ||