The author introduces the G-Mapper algorithm as a method to optimize the cover selection for Mapper graphs, utilizing statistical tests and Gaussian Mixture Models. This approach aims to improve the accuracy and efficiency of generating Mapper graphs.
Optimizing cover selection in Mapper graphs using G-means clustering for efficient visualization.
G-Mapper optimizes cover parameter using G-means clustering for Mapper construction.