A comparison of unsupervised dimension reduction algorithms for classification

Jaegul Choo, Hyunsoo Kim, Haesun Park, Hongyuan Zha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Distance preserving dimension reduction (DPDR) using the singular value decomposition has recently been introduced. In this paper, for disease diagnosis using gene or protein expression data, we present empirical comparison results between DPDR and other various dimension reduction (DR) methods (i.e. PCA, MDS, Isomap, and LLE) when using support vector machines with radial basis function kernel. Our results show that DPDR outperforms, as a whole, other DR methods in terms of classification accuracy, but at the same time, it gives significant efficiency compared with other methods since it has no parameter to be optimized. Based on these empirical results, we reach a promising conclusion that DPDR is one of the best DR methods at hand for modeling an efficient and distortion-free classifier for gene or protein expression data.

Original languageEnglish
Title of host publicationProceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007
Pages71-77
Number of pages7
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007 - Fremont, CA, United States
Duration: 2007 Nov 22007 Nov 4

Publication series

NameProceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007

Conference

Conference2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007
CountryUnited States
CityFremont, CA
Period07/11/207/11/4

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science(all)
  • Biomedical Engineering

Fingerprint Dive into the research topics of 'A comparison of unsupervised dimension reduction algorithms for classification'. Together they form a unique fingerprint.

  • Cite this

    Choo, J., Kim, H., Park, H., & Zha, H. (2007). A comparison of unsupervised dimension reduction algorithms for classification. In Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007 (pp. 71-77). [4413039] (Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007). https://doi.org/10.1109/BIBM.2007.51