Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Ensemble

  • Zhi-Hua Zhou
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_768

Synonyms

Classifier combination; Committee-based learning; Multiple classifier system

Definition

Ensemble is a learning paradigm where multiple learners are trained to solve the same problem. In contrast to ordinary learning approaches that try to learn one hypothesis from training data, ensemble methods try to construct and combine a set of hypotheses.

Historical Background

It is difficult to trace the starting point of the history of ensemble methods since the basic idea of deploying multiple models has been in use for a long time. However, it is clear that the hot wave of research on ensemble methods since the 1990s owes much to two works. The first is an applied research conducted by Hansen and Salamon at the end of 1980s [1], where they found that predictions made by the combination of a set of neural networks are often more accurate than predictions made by the best single neural network. The second is a theoretical research conducted in 1990, where Schapire proved that weak...

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Recommended Reading

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.National Key Lab for Novel Software TechnologyNanjing UniversityNanjingChina

Section editors and affiliations

  • Kyuseok Shim
    • 1
  1. 1.School of Elec. Eng. and Computer ScienceSeoul National Univ.SeoulRepublic of Korea