Name
Abstract | ||
|---|---|---|
Persistent homology is a method from computational algebraic topology that can be used to study the ``shapeu0027u0027 of data. We illustrate two filtrations --- the weight rank clique filtration and the Vietoris--Rips (VR) filtration --- that are commonly used in persistent homology, and we apply these filtrations to a pair of data sets that are both related to the 2016 European Union ``Brexitu0027u0027 referendum in the United Kingdom. These examples consider a topical situation and give useful illustrations of the strengths and weaknesses of these methods. |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Computational Geometry | Topological data analysis,Discrete mathematics,Brexit,Algebraic topology,Clique,Pure mathematics,Persistent homology,Strengths and weaknesses,Mathematics,European union |
DocType | Volume | Citations |
Journal | abs/1610.00752 | 5 |
PageRank | References | Authors |
0.53 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bernadette J. Stolz | 1 | 5 | 0.53 |
| Heather A. Harrington | 2 | 42 | 5.46 |
| Mason A. Porter | 3 | 748 | 66.14 |