Stitch Fix for Mapper and Topological Gains
This work addresses a specific technical challenge in topological data analysis for researchers in that field, representing an incremental advancement.
The paper tackles the problem of combining univariate mappers into bivariate mappers in topological data analysis, resulting in a method to stitch them together and visualize topological gains during this process.
The mapper construction is a powerful tool from topological data analysis that is designed for the analysis and visualization of multivariate data. In this paper, we investigate a method for stitching a pair of univariate mappers together into a bivariate mapper, and study topological notions of information gains, referred to as topological gains, during such a process. We further provide implementations that visualize such topological gains for mapper graphs.