| Abstract [eng] |
The main topic of this paper is mixed data clustering analysis and implementation. Clustering algorithm was implemented based on J. Liang, et al., Determining the number of clusters using information entropy for mixed data, Pattern Recognition (2012), doi:10.1016/j.patcog.2011.12.017 paper. Main contributions are: mixed datatype visualization using multidimensional scaling method, non random initial centers selection, validation of clustering results using Dunn and Davies- Bouldin indices. Modified algorithm was tested with synthetical and real data sets. Originally real data sets were with known groups, but before clustering labels from real data sets were removed. In all cases the number of true clusters were detected correctly. |
