Classification of proteomic data with logistic kernel partial least squares algorithm

Zhenqiu Liu; Dechang Chen; Jianjun Tian

doi:10.1109/CVPR.2005.430

Classification of proteomic data with logistic kernel partial least squares algorithm

Zhenqiu Liu, Dechang Chen, Jianjun Tian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
Publisher	IEEE Computer Society
ISBN (Electronic)	0769526608
DOIs	https://doi.org/10.1109/CVPR.2005.430
State	Published - 2005
Externally published	Yes
Event	2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops - San Diego, United States Duration: 21 Sep 2005 → 23 Sep 2005

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2005-September
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
Country/Territory	United States
City	San Diego
Period	21/09/05 → 23/09/05

Access to Document

10.1109/CVPR.2005.430

Cite this

Liu, Z., Chen, D., & Tian, J. (2005). Classification of proteomic data with logistic kernel partial least squares algorithm. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2005-September). IEEE Computer Society. https://doi.org/10.1109/CVPR.2005.430

@inproceedings{af339a5ef6c644019962288fc460e328,

title = "Classification of proteomic data with logistic kernel partial least squares algorithm",

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.",

author = "Zhenqiu Liu and Dechang Chen and Jianjun Tian",

note = "Publisher Copyright: {\textcopyright} 2005 IEEE Computer Society. All rights reserved.; 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops ; Conference date: 21-09-2005 Through 23-09-2005",

year = "2005",

doi = "10.1109/CVPR.2005.430",

language = "English",

series = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",

publisher = "IEEE Computer Society",

booktitle = "2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops",

}

Liu, Z, Chen, D & Tian, J 2005, Classification of proteomic data with logistic kernel partial least squares algorithm. in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2005-September, IEEE Computer Society, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops, San Diego, United States, 21/09/05. https://doi.org/10.1109/CVPR.2005.430

Classification of proteomic data with logistic kernel partial least squares algorithm. / Liu, Zhenqiu; Chen, Dechang; Tian, Jianjun.
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops. IEEE Computer Society, 2005. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2005-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Classification of proteomic data with logistic kernel partial least squares algorithm

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