Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS)
Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy · Society for Industrial and Applied Mathematics eBooks · 2022
Repeated Cross-Sectional (RCS) data measures a phenomenon by repeatedly sampling new cases from a population at successive measurement moments. It allows for analyzing societal trends without the need to follow individuals. To gain a deeper understanding of these trends, we propose EMM-RCS, an Exceptional Model Mining instance designed to find subgroups displaying exceptional trend behavior in RCS data. We build quality measures on the standard error, finding various types of exceptionalities within trends (exceptional flattening, slope, deviation from the norm). Additionally, EMM-RCS can handle practical RCS data problems, including uneven spacing of measurements over time, fluctuating sample sizes, and missing data.