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Supervised Learning

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Encyclopedia of the Sciences of Learning

Synonyms

Active learning; Classification; Inductive machine learning; Learning from labeled data; Learning with a teacher; Regression; Semi-supervised learning; Supervised machine learning

Definition

Supervised Learning is a machine learning paradigm for acquiring the input-output relationship information of a system based on a given set of paired input-output training samples. As the output is regarded as the label of the input data or the supervision, an input-output training sample is also called labeled training data, or supervised data. Occasionally, it is also referred to as Learning with a Teacher (Haykin 1998), Learning from Labeled Data, or Inductive Machine Learning (Kotsiantis 2007). The goal of supervised learning is to build an artificial system that can learn the mapping between the input and the output, and can predict the output of the system given new inputs. If the output takes a finite set of discrete values that indicate the class labels of the input, the learned...

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References

  • Haykin, S. (1998). Neural networks: A comprehensive foundation (2nd ed.). Upper Saddle River: Prentice Hall. ISBN 0-132-73350-1.

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  • Kotsiantis, S. (2007). Supervised machine learning: A review of classification techniques. Informatica Journal, 31, 249–268.

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  • Vapnik, V. (1995). The nature of statistical learning theory. New York: Springer. ISBN 0-387-98780-0.

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  • Wikipedia. (2010). Supervised learning. http://en.wikipedia.org/wiki/Supervised_learning

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Correspondence to Qiong Liu .

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© 2012 Springer Science+Business Media, LLC

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Liu, Q., Wu, Y. (2012). Supervised Learning. In: Seel, N.M. (eds) Encyclopedia of the Sciences of Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_451

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  • DOI: https://doi.org/10.1007/978-1-4419-1428-6_451

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-1427-9

  • Online ISBN: 978-1-4419-1428-6

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