Percentile-based dimensionality reduction and clustering for ordinal data matrices
Conference
65th ISI World Statistics Congress 2025
Format: CPS Abstract - WSC 2025
Keywords: clustering, dimensionality_reduction, ordinal_data
Session: CPS 11 - Dimension Reduction and Clustering Techniques for High-Dimensional Data
Wednesday 8 October 4 p.m. - 5 p.m. (Europe/Amsterdam)
Abstract
In this work we propose a flexible and interpretable data driven combination of dimensionality reduction and clustering for ordinal data matrices based on percentiles, which are suitable location measures for ordinal data. We discuss the proposal using a subset of data coming from the World Values Survey Wave 7.