16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04) A Study of Selective Neighborhood-Based Na?ve Bayes for Efficient Lazy Learning Boca Raton, Florida November 15-November 17 ISBN: 0-7695-2236-X
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICTAI.2004.19
This paper studies two accuracy estimation techniques, global accuracy estimation and local accuracy estimation, under the algorithmic framework of the selective neighborhood-based na?ve Bayes (SNNB) for lazy classification, resulting in two concrete learning algorithms of linear computational complexity, SNNB-G and SNNB-L. Extensive experiments show that SNNB-L is more accurate than na?ve Baye, C4.5, and SNNB-G.
Citation:
Zhipeng Xie, "A Study of Selective Neighborhood-Based Na?ve Bayes for Efficient Lazy Learning," ictai, pp.758-760, 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04), 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||