k-means clustering algorithm implementation written in Go. The k-means clustering algorithm partitions a multi-dimensional data set into k clusters, where each data point belongs to the cluster with the nearest mean, serving as a prototype of the cluster.

This code is built upon the work of https://github.com/muesli/kmeans Just removed the features we considered unnecessary (such as charting), and the use of external dependencies so that the package is more self-contained.

We plan to add other distance functions besides the already implemented Euclidean distance