MULTIVARIATE TECHNIQUES FOR PARAMETER SELECTION AND DATA-ANALYSIS EXEMPLIFIED BY A STUDY OF PYRETHROID NEUROTOXICITY

被引：41

作者：

FORD, MG ^{[1
]}

LIVINGSTONE, DJ ^{[1
]}

机构：

[1] SMITH KLINE BEECHAM PHARMACEUT LTD,MED CHEM,WELWYN GARDEN CIT AL6 9AR,HERTS,ENGLAND

来源：

QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS | 1990年 / 9卷 / 02期

关键词：

cluster analysis; dimension reduction; Factor analysis; multicollinearity; multiple regression; non‐linear mapping; supervised and unsupervised learning;

D O I：

10.1002/qsar.19900090206

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

A large number of molecular descriptors (70) were calculated for a series of pyrethroid insecticides using the techniques of computational chemistry. Because the set of descriptors contains considerable redundancy, it is necessary to reduce the size of the data matrix while retaining useful information. Various techniques are available for investigation and reduction of large data sets. Several of these methods have been employed and the results of the different strategies compared. It is concluded that there is no preferred method but that each technique has advantages to offer and is complementary. Copyright © 1990 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim

引用

页码：107 / 114

页数：8

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