DevOps Articles

K-Means and SOM: Introduction to Popular Clustering Algorithms

by Although K-means is a simple vector quantization method and Kohonen SOM is a neural network model, they’re remarkably similar.

The goal of the algorithm is to find and group similar data objects into a number (K) of clusters. By ‘similar’ we mean data points that are both close to each other (in the Euclidean sense) and close to the same cluster center.

This paper describes how SOM networks can help clinicians/physicians easily understand statistical data from healthcare centers by providing intuitive visualizations.