COMPUTERIZED LEARNING MACHINES APPLIED TO CHEMICAL PROBLEMS - MULTICATEGORY PATTERN CLASSIFICATION BY LEAST SQUARES

被引：68

作者：

KOWALSKI, BR

JURS, PC

ISENHOUR, TL

REILLEY, CN

机构：

[1] Department of Chemistry, University of Washington, Seattle

[2] Department of Chemistry, University of North Carolina, Chapel Hill

来源：

ANALYTICAL CHEMISTRY | 1969年 / 41卷 / 06期

关键词：

D O I：

10.1021/ac60275a026

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

A least squares pattern classifier which is capable of both recognition and prediction has been developed for multicategory pattern classification. The method operates on an approximative calculation which develops a single weight vector to simultaneously classify patterns into any number of categories. The method is evaluated with various mass spectrometry problems and compared to binary pattern classifiers for both ease of implementation and accuracy of results. © 1969, American Chemical Society. All rights reserved.

引用

页码：695 / &

共 7 条

[1] COMPUTERIZED LEARNING MACHINES APPLIED TO CHEMICAL PROBLEMS - INVESTIGATION OF CONVERGENCE RATE AND PREDICTIVE ABILITY OF ADAPTIVE BINARY PATTERN CLASSIFIERS [J].