Fused adjacency matrices to enhance information extraction: The beer benchmark.
Analytica Chimica Acta(2019)
摘要
Multivariate exploratory data analysis allows revealing patterns and extracting information from complex multivariate data sets. However, highly complex data may not show evident groupings or trends in the principal component space, e.g. because the variation of the variables are not grouped but rather continuous. In these cases, classical exploratory methods may not provide satisfactory results when the aim is to find distinct groupings in the data.
更多查看译文
关键词
Data fusion,Adjacency matrix,Clustering,Data visualization,Spectroscopy,Beer
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络