Choosing a suitable filtering function for the Mapper algorithm can be difficult due to its arbitrariness and domain-specific requirements. Finding a general filtering function that can be applied across domains is therefore of interest, since it would improve the representation of manifolds in higher dimensions. In this extended abstract, we propose that topological autoencoders is a suitable candidate for this and report initial results strengthening this hypothesis for one set of high-dimensional manifolds. The results indicate a potential for an easier choice of filtering function when using the Mapper algorithm, allowing for a more general and descriptive representation of high-dimensional data.
翻译:用于 Mapper 算法的适当过滤功能可能因其任意性和特定域的要求而难以选择。 因此,找到一个可以应用于不同域的一般过滤功能是值得注意的,因为这将改善更高维度的多个元的表示。 在这个扩展的抽象中,我们提议,地形自动编码器是适合这个选项的,并报告初步结果,加强一套高维元的假设。结果显示,在使用 Mapper 算法时,有可能更容易选择过滤功能,从而允许对高维数据作更一般和描述性的表示。