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Modelling of Clusters

  • Kurt Varmuza
Part of the Lecture Notes in Chemistry book series (LNC, volume 21)

Abstract

A usual pattern recognition problem in chemistry is to determine whether or not a compound is of a given type. The assumption often made that all patterns belonging to the same class form a distinct cluster is often unrealistic. An asymmetric situation occurs if one class does not form a proper homogeneous group [7]. In Figure 40 the patterns of class 1 form a rather compact cluster while class 2 is scattered throughout the whole pattern space. In a practical example, class 1 may correspond to “good” samples and class 2 to “bad” samples (equivalent to outliers whose features differ markedly from standard values). In such a case, it is useful to construct a model of class 1. The model is utilized either for the classification of unknown patterns or for the interpretation of the data structure. A confidence region can be constructed around the class model. Patterns outside this region are considered to belong to the “unstructured” class.

Keywords

Carbonyl Compound Principle Component Analysis Confidence Region Critical Radius Pattern Recognition Method 
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 Berlin Heidelberg 1980

Authors and Affiliations

  • Kurt Varmuza
    • 1
  1. 1.Institut für Allgemeine ChemieTechnischen Universität WienWienAustria

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