Mitchell’s, (1982, 1997) candidate-elimination algorithm performs a bidirectional search in the hypothesis space. It maintains a set, S, of most specific hypotheses that are consistent with the training data and a set, G, of most general hypotheses consistent with the training data. These two sets form two boundaries on the version space. See Learning as Search.
This is a preview of subscription content, log in via an institution to check access.
Recommended Reading
Mitchell, T. M. (1982). Generalization as search. Artificial Intelligence, 18(2), 203–226.
Mitchell, T. M. (1997). Machine learning. New York: McGraw-Hill.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this entry
Cite this entry
(2011). Candidate-Elimination Algorithm. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_91
Download citation
DOI: https://doi.org/10.1007/978-0-387-30164-8_91
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-30768-8
Online ISBN: 978-0-387-30164-8
eBook Packages: Computer ScienceReference Module Computer Science and Engineering