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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Cluster Analysis
verfasst von : Alan Julian Izenman
Erschienen in: Modern Multivariate Statistical Techniques
Verlag: Springer New York
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Cluster analysis
, which is the most well-known example of
unsupervised learning
, is a very popular tool for analyzing unstructured multivariate data. Within the data-mining community, cluster analysis is also known as
data segmentation
, and within the machine-learning community, it is also known as
class discovery
. The methodology consists of various algorithms each of which seeks to organize a given data set into homogeneous subgroups, or “clusters.” There is no guarantee that more than one such group can be found; however, in any practical application, the underlying hypothesis is that the data form a heterogeneous set that should separate into natural groups familiar to the domain experts.