The duality diagram in data analysis: Examples of modern applications

TL;DR

The paper revisits the duality diagram approach, illustrating its modern applications in data integration and showing its relevance as a precursor to kernel methods in complex data analysis.

Contribution

It introduces the duality diagram technique, demonstrating its new uses with various metrics and combinations, and connects it to modern kernel-based approaches.

Findings

Provides contemporary examples of duality diagrams in data integration

Shows the technique's versatility with different metrics and diagram combinations

Highlights the duality diagram as a precursor to kernel methods

Abstract

Today's data-heavy research environment requires the integration of different sources of information into structured data sets that can not be analyzed as simple matrices. We introduce an old technique, known in the European data analyses circles as the Duality Diagram Approach, put to new uses through the use of a variety of metrics and ways of combining different diagrams together. This issue of the Annals of Applied Statistics contains contemporary examples of how this approach provides solutions to hard problems in data integration. We present here the genesis of the technique and how it can be seen as a precursor of the modern kernel based approaches.