[2509.04603] DRtool: An Interactive Tool for Analyzing High-Dimensional Clusterings

Statistics > Applications arXiv:2509.04603 (stat) [Submitted on 4 Sep 2025 (v1), last revised 3 Apr 2026 (this version, v3)] Title:DRtool: An Interactive Tool for Analyzing High-Dimensional Clusterings Authors:Justin Lin, Julia Fukuyama View a PDF of the paper titled DRtool: An Interactive Tool for Analyzing High-Dimensional Clusterings, by Justin Lin and Julia Fukuyama View PDF HTML (experimental) Abstract:When faced with new data, we often conduct a cluster analysis to obtain a better understanding of the data's structure and the archetypical samples present in the data. This process often includes visualization of the data, either as a way to discover or verify clusters. However, the increases in data complexity and dimensionality has made this step very tricky. To visualize data, nonlinear dimension reduction methods are the de facto standard for their ability to non-uniformly stretch and shrink space in order to preserve local clusters. Because this process requires a drastic manipulation of space, however, nonlinear dimension reduction methods are known to produce false structures, especially when mishandled. A common consequence that often goes undetected by the untrained eye is over-clustering of the data. In efforts to deal with this phenomenon, we developed an interactive tool that empowers analysts to distinguish false clusters and better interpret their high-dimensional clustering results. The tool uses various analytical plots to provide a multi-faceted perspe...