Support Vector Machines and Their Application in Chemistry and Biotechnology

by Yizeng Liang, Qing-Song Xu, Hong-Dong Li, Dong-Sheng Cao

Overview

Support vector machines (SVMs) are used in a range of applications, including drug design, food quality control, metabolic fingerprint analysis, and microarray data-based cancer classification. While most mathematicians are well-versed in the distinctive features and empirical performance of SVMs, many chemists and biologists are not as familiar wi

Product Details

ISBN-13:	9781040053249
Publisher:	CRC Press
Publication date:	04/19/2016
Sold by:	Barnes & Noble
Format:	eBook
Pages:	211
File size:	4 MB

About the Author

Yizeng Liang and Qing-Song Xu are with Central South University in Changsha, China.

Table of Contents

Overview of support vector machines. Support vector machines for classification and regression. Kernel methods. Ensemble learning of support vector machines. Support vector machines applied to near-infrared spectroscopy. Support vector machines and QSAR/QSPR. Support vector machines applied to traditional Chinese medicine. Support vector machines applied to OMICS study. Index.