Classification of proteomic data with logistic kernel partial least squares algorithm

Zhenqiu Liu, Dechang Chen, Jianjun Tian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we introduce the logistic kernel partial least squares (LKPLS) algorithm for classification of health vs. cancer using mass spectrometry (MS). Wavelet decomposition is proposed for feature selection and data preprocessing. LKPLS combines the logistic regression with the kernel partial least squares algorithm. The method is applied to real life cancer samples. Experimental comparisons show that LKPLS outperforms other methods in the analysis of MS data.

Original languageEnglish
Title of host publication2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
PublisherIEEE Computer Society
ISBN (Electronic)0769526608
DOIs
StatePublished - 2005
Externally publishedYes
Event2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops - San Diego, United States
Duration: 21 Sep 200523 Sep 2005

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2005-September
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
Country/TerritoryUnited States
CitySan Diego
Period21/09/0523/09/05

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