View source for Repeated incremental pruning to produce error reduction (RIPPER)

In [[machine learning]], '''repeated incremental pruning to produce error reduction''' (RIPPER) is a propositional [[Rule-based machine learning|rule learner]] proposed by William W. Cohen as an optimized version of IREP.<ref name="Agah">{{cite book|last1=Agah|first1=Arvin|title=Medical Applications of Artificial Intelligence|date=2013|publisher=CRC Press|isbn=9781439884331|url=https://books.google.com/books?id=nWVmAQAAQBAJ&pg=PA37&dq=Repeated+Incremental+Pruning+to+Produce+Error+Reduction#q=Repeated%20Incremental%20Pruning%20to%20Produce%20Error%20Reduction|accessdate=13 August 2017|language=en}}</ref>
==References==
{{reflist}}
==Links==
* [https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Classification/JRip Data Mining Algorithms In R/Classification/JRip]
[[Category:Machine learning algorithms]]