# A close-up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation

arXiv: https://arxiv.org/abs/1907.11505 · HTML: https://mlsanity.com/paper/1907.11505/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [Normalised clustering accuracy: An asymmetric external cluster validity measure](https://mlsanity.com/paper/2209.02935/) (2022)

## Abstract (arXiv)

The misclassification error distance and the adjusted Rand index are two of the most commonly used criteria to evaluate the performance of clustering algorithms. This paper provides an in-depth comparison of the two criteria, aimed to better understand exactly what they measure, their properties and their differences. Starting from their population origins, the investigation includes many data analysis examples and the study of particular cases in great detail. An exhaustive simulation study allows inspecting the criteria distributions and reveals some previous misconceptions.