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.
童逸夫, 黄春毅. 多维多息特征数据挖掘方法研究——以中药指纹图谱数据为例[J]. 现代图书情报技术, 2011, 27(12): 69-73.
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.
