Visualizing Classification Structure of Large-Scale Classifiers
Not on the map. Why?
Abstract (arXiv)
We propose a measure to compute class similarity in large-scale classification based on prediction scores. Such measure has not been formally pro-posed in the literature. We show how visualizing the class similarity matrix can reveal hierarchical structures and relationships that govern the classes. Through examples with various classifiers, we demonstrate how such structures can help in analyzing the classification behavior and in inferring potential corner cases. The source code for one example is available as a notebook at https://github.com/bilalsal/blocks
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 12 Jul 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1.
1 paper.