$G$-Mapper: Learning a Cover in the Mapper Construction

arXiv:2309.06634v2 Announce Type: replace
Abstract: The Mapper algorithm is a visualization technique in topological data analysis (TDA) that outputs a graph reflecting the structure of a given dataset. However, the Mapper algorithm requires tuning several parameters in order to generate a ``nice" Mapper graph. This paper focuses on selecting the cover parameter. We present an algorithm that optimizes the cover of a Mapper graph by splitting a cover repeatedly according to a statistical test for normality. Our algorithm is based …

abstract algorithm analysis arxiv construction cs.lg data data analysis dataset generate graph math.at nice paper parameters stat.ml type visualization