Jump to content

Instance-based learning

From Wikipedia, the free encyclopedia
This is an old revision of this page, as edited by SmackBot (talk | contribs) at 15:19, 28 April 2009 (Date maintenance tags and general fixes). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

In machine learning, instance-based learning is a name for a family of learning algorithms. It is also referred to as memory-based learning. It's called instance-based because it constructs hypotheses directly from the training instances themselves.[1] This means that the hypothesis complexity can grow with the data.[1]

A simple example of an instance-based learning algorithm is the k-nearest neighbour algorithm.

References

  1. ^ a b Russel, Stuart and Norvig, Peter: Artificial Intelligence: A Modern Approach, second edition, page 733. Prentice Hall, 2003. ISBN 0-13-080302-2


Stub icon

This artificial intelligence-related article is a stub. You can help Wikipedia by expanding it.

Retrieved from "https://en.wikipedia.org/w/index.php?title=Instance-based_learning&oldid=286659439"