Applied-Information Technology in Fusion SVM Partial Least Squares Analysis of Experimental Data in the Body of PET

Xian Zhou; Ying Xiong; Wang Ping Xiong; Ling Zhu Xiong

doi:10.4028/www.scientific.net/AMR.951.185

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 951Applied-Information Technology in Fusion SVM...

Applied-Information Technology in Fusion SVM Partial Least Squares Analysis of Experimental Data in the Body of PET

Abstract:

Experimental data for the human body PET multi-variable, non-linear distribution and other characteristics, the use of fusion partial least squares support vector machine variables effectively extracted from the principal component, reducing the number of variables and the exclusion of noise information to construct a linear regression with the dependent variables model, fitting the model has good accuracy and generalization for PET clinical trials provide effective technical support and research ideas.

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Periodical:

Advanced Materials Research (Volume 951)

Pages:

185-188

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.951.185

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Online since:

May 2014

Authors:

Xian Zhou, Ying Xiong, Wang Ping Xiong*, Ling Zhu Xiong

Keywords:

Data Mining (DM), Nonlinear Data, Partial Least Squares, PET, SVM

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