Abstract:

One of the stages in cluster analysis, carried out on the basis of metric data (interval, ratio), is the choice of variable normalization method. This paper presents the proposal of two procedures (for clustering algorithms based on distance matrix and data matrix), which allows for the isolation of the groups of normalization methods that lead to similar clustering results. The proposal can reduce the problem of choosing the normalization method in cluster analysis. The results are illustrated via simulation study and empirical example with application of clusterSim package and R program.