Statistical Parameter Selection for Clustering Persistence Diagrams

摘要: In urgent decision making applications, ensemble simulations are an important way to determine different outcome scenarios based on currently available data. this paper, we will analyze the output of by considering socalled persistence diagrams, which reduced representations original data, motivated extraction topological features. Based a recently published progressive algorithm for clustering optimal number clusters, and therefore significantly scenarios, minimization established statistical score functions. Furthermore, present proof-ofconcept prototype implementation selection clusters provide results experimental study, where has been applied real-world data sets.