# K-Means Kernel Classifier

arXiv: https://arxiv.org/abs/2012.13021 · HTML: https://mlsanity.com/paper/2012.13021/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Dec 2020.

## Built on by (most cited first, 2 of 2)

- [Diffusion Self-Organizing Map on the Hypersphere](https://mlsanity.com/paper/2106.00014/) (2021)
- [ELM Ridge Regression Boosting](https://mlsanity.com/paper/2310.16209/) (2023)

## Abstract (arXiv)

We combine K-means clustering with the least-squares kernel classification method. K-means clustering is used to extract a set of representative vectors for each class. The least-squares kernel method uses these representative vectors as a training set for the classification task. We show that this combination of unsupervised and supervised learning algorithms performs very well, and we illustrate this approach using the MNIST dataset