论文标题
映射图的热点标识
Hotspot identification for Mapper graphs
论文作者
论文摘要
映射器算法可用于构建基于图形的高维数据的表示形式，以捕获结构上有趣的功能，例如环，耀斑或簇。可以通过对顶点的附加着色来进一步注释该图，从而允许特殊关注区域的位置。例如，在许多应用程序中，例如精密医学，映射器图已被用来识别数据集中未知的紧凑型局部群体，以表明独特或不寻常的行为。该任务是由研究人员执行的，可以使用热点分析自动化。在这项工作中，我们提出了一种用于检测映射图中热点的新算法。它允许自动化热点检测过程。我们在许多人造和现实世界数据集上演示了该算法的性能。我们进一步证明了如何将算法用于映射器镜头函数的自动选择。
Mapper algorithm can be used to build graph-based representations of high-dimensional data capturing structurally interesting features such as loops, flares or clusters. The graph can be further annotated with additional colouring of vertices allowing location of regions of special interest. For instance, in many applications, such as precision medicine, Mapper graph has been used to identify unknown compactly localized subareas within the dataset demonstrating unique or unusual behaviours. This task, performed so far by a researcher, can be automatized using hotspot analysis. In this work we propose a new algorithm for detecting hotspots in Mapper graphs. It allows automatizing of the hotspot detection process. We demonstrate the performance of the algorithm on a number of artificial and real world datasets. We further demonstrate how our algorithm can be used for the automatic selection of the Mapper lens functions.
