Principal component analysis for bar charts and metabins tables

摘要

Abstract In recent years, the analysis of symbolic data where the units are categories, classes, or concepts described by intervals, distributions, sets of categories, and the like becomes a challenging task since many application fields generate complex and massive amounts of data that are difficult to analyze with traditional techniques. In this article, we propose a strategy for extending standard principal component analysis (PCA) to such data in the case where the variables values are `bar.