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New Technology of Library and Information Service  2011, Vol. 27 Issue (12): 69-73    DOI: 10.11925/infotech.1003-3513.2011.12.11
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Research on Data Mining of Complex Multi-dimensional Fingerprint Data of TCM
Tong Yifu, Huang Chunyi
School of Public Administration, Sichuan University, Chengdu 610064, China
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Abstract  Grounded on the R open source statistic environment, this paper builds a data mining model on the complex HPLC multi-dimensional fingerprint data with visualization analysis. The result fully reflects that PCA can be used as a model to reveal the principles of multi-dimensional data, and verifies the validity and practicality of principal component and cluster analysis and neural network to reveal the character of multi-dimensional data. Finally, based on the results of PCA and cluster analysis, this paper builds a training network model through techniques of machine learning and other related statistical algorithm to predict the habitat of unknown TCM sample, which supplies sufficient evidences to the TCM quality control.
Key wordsMulti-dimensional information      Data mining      Principal component and cluster analysis      Neural network     
Received: 25 October 2011      Published: 02 February 2012



Cite this article:

Tong Yifu, Huang Chunyi. Research on Data Mining of Complex Multi-dimensional Fingerprint Data of TCM. New Technology of Library and Information Service, 2011, 27(12): 69-73.

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