The newest results in the application of cluster analysis a multivariate mathematical-statistical technique for the evaluation of large
retention data matrices are collected. The results are critically evaluated, and examples for the application in gas chromatography, liquid
chromatographic techniques such as thin-layer chromatography and high-performance liquid chromatography, as well as in electrically
driven systems are presented.
Key words: cluster analysis; dendograms; Euclidean distance; average linkage; 3-D diagram of clusters; food and food products; health care; plant materials
|
