Time-varying topological simplifications of the space of votes in the US House of Representatives (US HoR) display several interesting features unavailable with classical methods of machine learning. In this paper we demonstrate how a re- cently developed topological simplification method, MAPPER, can detect changes in collaboration structures within the US HoR over time.
QC 20130523