The Choice of Variable Normalization Method in Cluster Analysis
Andrzej Dudek , Marek Walesiak
AbstractOne 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.
|Publication size in sheets||0.75|
|Book||Soliman Khalid S. (eds.): Education Excellence and Innovation Management: A 2025 Vision to Sustain Economic Development during Global Challenges, 2020, International Business Information Management Association (IBIMA), ISBN 9780999855141|
|Keywords in English||Normalization of Variables, Cluster Analysis, Real Estate Market, Clustersim|
|Uwaga||The project is financed by the Ministry of Science and Higher Education in Poland under the program “Regional Initiative of Excellence” 2019-2022, project number 015/RID/2018/19, total funding amount 10,721,040 PLN.|
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