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.


Acute Myeloid Leukemia Acute Lymphoblastic Leukemia Component Plane Acute Myeloid Leukemia Sample Block 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 Science+Business Media New York 2013

Authors and Affiliations

  • Alan Julian Izenman
    • 1
  1. 1.Department of StatisticsTemple UniversityPhiladelphiaUSA

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