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NNMap: A method to construct a good embedding for nearest neighbor classification
Jing Chen1,2; Yuan Yan Tang1,2; C. L. Philip Chen1; Bin Fang2; Zhaowei Shang2; Yuewei Lin3
2015-03-25
Source PublicationNeurocomputing
ISSN0925-2312
Volume152Pages:97-108
Abstract

This paper aims to deal with the practical shortages of nearest neighbor classifier. We define a quantitative criterion of embedding quality assessment for nearest neighbor classification, and present a method called NNMap to construct a good embedding. Furthermore, an efficient distance is obtained in the embedded vector space, which could speed up nearest neighbor classification. The quantitative quality criterion is proposed as a local structure descriptor of sample data distribution. Embedding quality corresponds to the quality of the local structure. In the framework of NNMap, one-dimension embeddings act as weak classifiers with pseudo-losses defined on the amount of the local structure preserved by the embedding. Based on this property, the NNMap method reduces the problem of embedding construction to the classical boosting problem. An important property of NNMap is that the embedding optimization criterion is appropriate for both vector and non-vector data, and equally valid in both metric and non-metric spaces. The effectiveness of the new method is demonstrated by experiments conducted on the MNIST handwritten dataset, the CMU PIE face images dataset and the datasets from UCI machine learning repository.

KeywordEmbedding Methods Embedding Quality Nearest Neighbor Classification Non-metric Distance
DOIhttps://doi.org/10.1016/j.neucom.2014.11.014
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000349572600011
PublisherELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
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Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorJing Chen
Affiliation1.Faculty of Science and Technology, University of Macau, Taipa, Macau, China
2.Chongqing University, Chongqing, China
3.University of South Carolina, Columbia, USA
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Jing Chen,Yuan Yan Tang,C. L. Philip Chen,et al. NNMap: A method to construct a good embedding for nearest neighbor classification[J]. Neurocomputing,2015,152:97-108.
APA Jing Chen,Yuan Yan Tang,C. L. Philip Chen,Bin Fang,Zhaowei Shang,&Yuewei Lin.(2015).NNMap: A method to construct a good embedding for nearest neighbor classification.Neurocomputing,152,97-108.
MLA Jing Chen,et al."NNMap: A method to construct a good embedding for nearest neighbor classification".Neurocomputing 152(2015):97-108.
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