Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/62091
Type: Artigo de periódico
Title: Non-supervised pattern recognition methods: Exploring chemometrical procedures for evaluating analytical data
Author: Correia, PRM
Ferreira, MMC
Abstract: An activity for introducing hierarchical cluster analysis (HCA) and principal component analysis (PCA) during the Instrumental Analytical Chemistry course is presented. The posed problem involves the discrimination of mineral water samples according to their geographical origin. Thirty-seven samples of 9 different brands were considered and the results from the determination of Na, K, Mg, Ca, Sr and Ba were taken into account. Non-supervised methods for pattern recognition were explored to construct a dendrogram, score and loading plots. The devised activity can be adopted for introducing Chemometrics devoted to data handling, stressing its importance in the context of modem Analytical Chemistry.
Subject: analytical chemistry
chemometrics
pattern recognition
Country: Brasil
Editor: Soc Brasileira Quimica
Rights: aberto
Identifier DOI: 10.1590/S0100-40422007000200042
Date Issue: 2007
Appears in Collections:Unicamp - Artigos e Outros Documentos

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