Advertisement

Unsupervised Learning

  • Miroslav Kubat
Chapter

Abstract

It would be a mistake to think that machine learning always requires examples with class labels. Far from it! Useful information can be gleaned even from examples whose classes are not known. This is sometimes called unsupervised learning, in contrast to the term supervised learning which is used when talking about induction from pre-classified examples.

References

  1. 2.
    Ball, G. H. & Hall, D. J. (1965). ISODATA, a novel method of data analysis and clasification. Technical Report of the Standford University, Stanford, CAGoogle Scholar
  2. 45.
    Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43, 59–69MathSciNetCrossRefzbMATHGoogle Scholar
  3. 58.
    McQueen, J. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the 5th Berkeley symposium on mathematical statistics and probability, Berkeley (pp. 281–297).Google Scholar
  4. 71.
    Murty, M. N. & Krishna, G. (1980). A computationally efficient technique for data clustering. Pattern Recognition, 12, 153–158.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Miroslav Kubat
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of MiamiCoral GablesUSA

Personalised recommendations