A hierarchy of classification

The taxonomy of physical events in the night sky (erupting stars, stellar explosions, and even gravitational lensing) is inherently hierarchical in nature. Broad physical families subdivide into increasingly specific physics, forming a tree-structured classification problem. Standard classification objectives typically ignore said structure and treat all misclassifications equally, rather than encouraging classifiers to "make better mistakes". In this talk, I will discuss a few approaches to modeling hierarchical class structure within the objective function. I will also discuss open issues of "fuzzy boundaries" within this taxonomy, in which both discrete and continuous subclasses exist.

Astronomy

Classification

Machine Learning