A Study of Selective Neighborhood-Based Na?ve Bayes for Efficient Lazy Learning

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http://doi.ieeecomputersociety.org/10.1109/ICTAI.2004.19

16th IEEE International Conference on ...

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	ASCII Text	x
	Zhipeng Xie, "A Study of Selective Neighborhood-Based Na?ve Bayes for Efficient Lazy Learning," Tools with Artificial Intelligence, IEEE International Conference on, pp. 758-760, 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04), 2004.

	BibTex	x
	@article{ 10.1109/ICTAI.2004.19, author = {Zhipeng Xie}, title = {A Study of Selective Neighborhood-Based Na?ve Bayes for Efficient Lazy Learning}, journal ={Tools with Artificial Intelligence, IEEE International Conference on}, volume = {0}, year = {2004}, issn = {1082-3409}, pages = {758-760}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICTAI.2004.19}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Tools with Artificial Intelligence, IEEE International Conference on TI - A Study of Selective Neighborhood-Based Na?ve Bayes for Efficient Lazy Learning SN - 1082-3409 SP758 EP760 A1 - Zhipeng Xie, PY - 2004 KW - null VL - 0 JA - Tools with Artificial Intelligence, IEEE International Conference on ER -

Zhipeng Xie, Fudan University

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

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