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Supervised Learning: Partition Methods

  • Bertrand Clarke
  • Ernest Fokoué
  • Hao Helen Zhang
Chapter
Part of the Springer Series in Statistics book series (SSS)

Basically, supervised learning is what statisticians do almost all the time. The “supervision” refers to the fact that the Y is are available, in contrast to unsupervised learning, the topic of Chapter 8, where Y is are assumed unavailable. The term “learning” is used in a heuristic sense to mean any inferential procedure that can, in principle, be tested for validity. Having measurements on Y available means that model identification, decision making, prediction, and many other goals of analysis can all be validated.

Keywords

Support Vector Machine Support Vector Feature Space Random Forest Singular Value Decomposition 
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 New York 2009

Authors and Affiliations

  • Bertrand Clarke
    • 1
  • Ernest Fokoué
    • 2
  • Hao Helen Zhang
    • 3
  1. 1.University of MiamiMiamiCanada
  2. 2.Department of Science & MathematicsKettering UniversityFlintUSA
  3. 3.Department of StatisticsNorth Carolina State University Program in Statistical GeneticsRaleighUSA

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