عنوان

Support vector machines and their application in chemistry and biotechnology /

شابک

1439821275 (hardback)

شابک

9781439821275 (hardback)

کد کشور

bnb

شماره

b430404

عنوان اصلي

Support vector machines and their application in chemistry and biotechnology /

نام عام مواد

[Book]

نام نخستين پديدآور

Yizeng Liang ... [et al.]

محل نشرو پخش و غیره

Boca Raton :

نام ناشر، پخش کننده و غيره

CRC Press,

تاریخ نشرو بخش و غیره

c2011

نام خاص و کميت اثر

x, 201 p. :

ساير جزييات

ill. ;

ابعاد

24 cm

متن يادداشت

Includes bibliographical references and index

متن يادداشت

"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"--

متن يادداشت

"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"--

موضوع مستند نشده

Chemometrics

موضوع مستند نشده

Support vector machines

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Liang, Yizeng

تاريخ عمليات

20110616221557.0

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y