A method for clustering and screening of long-dimensional chemical data based on fingerprints and similarity measurements

被引：5

作者：

Urbano Cuadrado, Manuel ^{[1
]}

Cerruela Garcia, Gonzalo ^{[1
]}

Luque Ruiz, Irene ^{[1
]}

Angel Gomez-Nieto, Miguel ^{[1
]}

机构：

[1] Univ Cordoba, Dept Comp & Numer Anal, E-14071 Cordoba, Spain

来源：

JOURNAL OF MATHEMATICAL CHEMISTRY | 2006年 / 40卷 / 01期

关键词：

data preparation; similarity calculation; fingerprints; clustering; screening;

D O I：

10.1007/s10910-006-9118-5

中图分类号：

O6 [化学];

学科分类号：

0703 [化学];

摘要：

A method for the treatment of long-dimensional chemical data arrays is presented in this work with the aim of maximising classification models. The method is based on the construction of fingerprints and the subsequent generation of a similarity matrix. The similarity calculation has been modified through a scaling process to take into account different significance shown by the variables. The method was applied to spectral measurements of wines and several aspects were studied, namely: threshold considered in the construction of fingerprints and patterns, weighting factor used for scaling, normalisation method, etc. The application of both Principal Components Analysis and Soft-Independent Modelling of Class Analogies to the similarity matrices gave better classifications of the information than those obtained using original data.

引用

页码：15 / 27

页数：13

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