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.

翻译：映射算法可用于构建基于图表的高维数据的表达方式, 捕捉结构上有趣的特征, 如环形、 耀斑或星团。 图表可以进一步附加附加说明, 加上允许特别感兴趣的区域位置的脊椎颜色。 例如, 在许多应用中, 例如精密医学, 映射图被用于识别数据集中显示独特或异常行为的不明的缩略亚区域 。 由研究者完成的这一任务, 可以通过热点分析实现自动化 。 在这项工作中, 我们提出了用于在映射图中探测热点的新算法 。 它允许热点探测进程的自动化 。 我们演示了许多人造和真实世界数据集的算法性 。 我们进一步演示如何使用我们的算法来自动选择 映射镜函数 。