Applicational aspects of support vector machines

被引：154

作者：

Belousov, AI ^{[1
]}

Verzakov, SA ^{[1
]}

von Frese, J ^{[1
]}

机构：

[1] Inst Chem & Biochem Sensor Res, D-48149 Munster, Germany

来源：

JOURNAL OF CHEMOMETRICS | 2002年 / 16卷 / 8-10期

关键词：

classification; support vector machines; mid-infrared spectroscopy; polymer recognition;

D O I：

10.1002/cem.744

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The special emphasis of support vector machines (SVMs) on generalization ability makes this approach particularly interesting for real-world applications with limited amounts of training data. In this paper we analyse the applicational aspects of SVMs, illustrating them with the step-by-step construction of a classifier for polymers by means of their mid-infrared spectra. With this example we show how the main difficulties of a typical industrial classification task can be addressed using SVMs. (C) Copyright 2002 John Wiley Sons, Ltd.

引用

页码：482 / 489

页数：8

共 20 条

[1]

[Anonymous], 1998, Encyclopedia of Biostatistics

[2]

BELOUSOV AI, 2002, IN PRESS CHEMOMETRIC

[3] A tutorial on Support Vector Machines for pattern recognition [J].

Burges, CJC .

DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 2 (02) :121-167

[4] The influence of data pre-processing in the pattern recognition of excipients near-infrared spectra [J].

Candolfi, A ;

De Maesschalck, R ;

Jouan-Rimbaud, D ;

Hailey, PA ;

Massart, DL .

JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 1999, 21 (01) :115-132

[5]

Cristiani N., 2000, INTRO SUPPORT VECTOR

[6] Decision criteria for soft independent modelling of class analogy applied to near infrared data [J].

De Maesschalck, R ;

Candolfi, A ;

Massart, DL ;

Heuerding, S .

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1999, 47 (01) :65-77

[7] Training invariant support vector machines [J].

Decoste, D ;

Schölkopf, B .

MACHINE LEARNING, 2002, 46 (1-3) :161-190

[8] Support vector machines for spam categorization [J].

Drucker, H ;

Wu, DH ;

Vapnik, VN .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1999, 10 (05) :1048-1054

[9] On-line post consumer package identification by NIR spectroscopy combined with a FuzzyARTMAP classifier in an industrial environment [J].

Feldhoff, R ;

Wienke, D ;

Cammann, K ;

Fuchs, H .

APPLIED SPECTROSCOPY, 1997, 51 (03) :362-368

[10] Support vector machine classification and validation of cancer tissue samples using microarray expression data [J].

Furey, TS ;

Cristianini, N ;

Duffy, N ;

Bednarski, DW ;

Schummer, M ;

Haussler, D .

BIOINFORMATICS, 2000, 16 (10) :906-914

← 1 2 →