Feature Selection for Pattern Classification Problems

CC
CIT
2004
Fourth International Conference on Computer and Information Technology (CIT'04)
Abstract - Feature Selection for Pattern Classification Problems

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Fourth International Conference on Computer and Information Technology (CIT'04)

Wuhan, China

September 14-September 16

ISBN: 0-7695-2216-5

	ASCII Text	x
	Li Zhang, Gang Sun, Jun Guo, "Feature Selection for Pattern Classification Problems," Computer and Information Technology, International Conference on, pp. 233-237, Fourth International Conference on Computer and Information Technology (CIT'04), 2004.

	BibTex	x
	@article{ 10.1109/CIT.2004.1357202, author = {Li Zhang and Gang Sun and Jun Guo}, title = {Feature Selection for Pattern Classification Problems}, journal ={Computer and Information Technology, International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2216-5}, pages = {233-237}, doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357202}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer and Information Technology, International Conference on TI - Feature Selection for Pattern Classification Problems SN - 0-7695-2216-5 SP233 EP237 A1 - Li Zhang, A1 - Gang Sun, A1 - Jun Guo, PY - 2004 KW - null VL - 0 JA - Computer and Information Technology, International Conference on ER -

Li Zhang, Beijing University of Posts and Telecommunications

Gang Sun, Beijing University of Posts and Telecommunications

Jun Guo, Beijing University of Posts and Telecommunications

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357202

In pattern recognition feature selection is an important problem which is to choose the smallest subset of features that ideally is necessary and sufficient to describe the target concept. In this paper, a feature selection algorithm based on DB index rules is proposed involving classification capabilities of feature vectors and correlation analysis between two features. The strategy can be used for supervised or unsupervised classification problems and it is evaluated by using three synthetic data sets and a real-word data set.

Citation:

Li Zhang, Gang Sun, Jun Guo, "Feature Selection for Pattern Classification Problems," cit, pp.233-237, Fourth International Conference on Computer and Information Technology (CIT'04), 2004

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