# Hierarchy Representation of Data in Machine Learnings

arXiv: https://arxiv.org/abs/2402.09965 · HTML: https://mlsanity.com/paper/2402.09965/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 9 references that are in the map.
- First posted on arXiv 30 Nov 2023.

## Abstract (arXiv)

When there are models with clear-cut judgment results for several data points, it is possible that most models exhibit a relationship where if they correctly judge one target, they also correctly judge another target. Conversely, if most models incorrectly judge one target, they may also incorrectly judge another target. We propose a method for visualizing this hierarchy among targets. This information is expected to be beneficial for model improvement.