DocumentCode
3466637
Title
CN2-R: Faster CN2 with randomly generated complexes
Author
Zuters, J.
Author_Institution
Fac. of Comput., Univ. of Latvia, Riga, Latvia
fYear
2011
fDate
22-25 Aug. 2011
Firstpage
306
Lastpage
309
Abstract
Among the rule induction algorithms, the classic CN2 is still one of the most popular ones; a great amount of enhancements and improvements to it is to witness this. Despite the growing computing capacities since the algorithm was proposed, one of the main issues is resource demand. The proposed modification, CN2-R, substitutes the star concept of the original algorithm with a technique of randomly generated complexes in order to substantially improve on running times without significant loss in accuracy.
Keywords
knowledge based systems; learning (artificial intelligence); CN2-R; faster CN2; randomly generated complex; resource demand; rule induction algorithm; Accuracy; Algorithm design and analysis; Classification algorithms; Complexity theory; Iris; Machine learning; Machine learning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Methods and Models in Automation and Robotics (MMAR), 2011 16th International Conference on
Conference_Location
Miedzyzdroje
Print_ISBN
978-1-4577-0912-8
Type
conf
DOI
10.1109/MMAR.2011.6031363
Filename
6031363
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