Clustering for Microanalytical Data

  • Desiré L. Massart
Conference paper


Clustering is a chemometrical technique, used for the grouping or classification of objects characterized by multivariate analytical data. The hierarchical and non-hierarchical algorithms are discussed. Among the hierarchical methods the average linkageand Ward’s method are preferred, while the preferred non-hierarchical method is MASLOC. The latter is the only method with a build-in rule for the selection of significant clusters. The importance of combining clustering with other multivariate techniques, such as factor analysis, is stressed.


Hierarchical Cluster Significant Cluster Seed Point Iron Meteorite Natural Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag/Wien 1981

Authors and Affiliations

  • Desiré L. Massart
    • 1
  1. 1.Farmaceutisch InstituutVrije Universiteit BrusselBrusselsBelgium

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