Repeated incremental pruning to produce error reduction (RIPPER)

In machine learning, repeated incremental pruning to produce error reduction (RIPPER) is a propositional rule learner proposed by William W. Cohen as an optimized version of IREP.[1]

References
  1. Agah, Arvin (2013). Medical Applications of Artificial Intelligence. CRC Press. ISBN 9781439884331. Retrieved 13 August 2017.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.