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Feature selection based on loss-margin of nearest neighbor classification
- Source :
-
Pattern Recognition . Sep2009, Vol. 42 Issue 9, p1914-1921. 8p. - Publication Year :
- 2009
-
Abstract
- Abstract: The problem of selecting a subset of relevant features is classic and found in many branches of science including—examples in pattern recognition. In this paper, we propose a new feature selection criterion based on low-loss nearest neighbor classification and a novel feature selection algorithm that optimizes the margin of nearest neighbor classification through minimizing its loss function. At the same time, theoretical analysis based on energy-based model is presented, and some experiments are also conducted on several benchmark real-world data sets and facial data sets for gender classification to show that the proposed feature selection method outperforms other classic ones. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 00313203
- Volume :
- 42
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- Pattern Recognition
- Publication Type :
- Academic Journal
- Accession number :
- 40112543
- Full Text :
- https://doi.org/10.1016/j.patcog.2008.10.011